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Preprint ARTICLE | doi:10.20944/preprints202201.0061.v1

EmmDocClassifier: Efficient Multimodal Document Image Classifier for Scarce Data

Shrinidhi Kanchi, Alain Pagani, Hamam Mokayed, Marcus Liwicki, Didier Stricker, Muhammad Zeshan Afzal

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: BERT, Document Image Classification, EfficientNet, fine-tuned BERT, Hierarchical Attention Networks, Multimodal, RVL-CDIP, Two-stream, Tobacco-3482

Online: 6 January 2022 (10:08:38 CET)

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Preprint ARTICLE | doi:10.20944/preprints202004.0507.v1

Virus Graph and COVID-19 Pandemic: A Graph Theory Approach

H. R. Bhapkar, Parikshit Mahalle, Prashant S. Dhotre

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: virus graphs; COVID-19; pandemic; epidemic

Online: 29 April 2020 (12:32:24 CEST)

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Working Paper COMMUNICATION

Mid-Low Resolution Remote Sensing Ship Detection Using Super-Resolved Feature Representation

Shitian He, Huanxin Zou, Yingqian Wang, Runlin Li, Fei Cheng, Xu Cao

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Ship detection; image super-resolution; mid-low resolution remote sensing images

Online: 16 August 2021 (12:51:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201902.0252.v2

A Secure and Optimal Method of Steganography Using Bit Combination and Dynamical Rotation over Addresses

Moses Okello

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: General Mathematics, Combinatorial, Algebra, Steganography, Probability, Cryptography

Online: 20 March 2019 (15:43:30 CET)

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Preprint ARTICLE | doi:10.20944/preprints201607.0037.v1

THE AVERAGE LOWER 2-DOMINATION NUMBER OF WHEELS RELATED GRAPHS AND AN ALGORITHM

TUFAN TURACI

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: graph vulnerability; connectivity; network design and communication; domination number; average lower 2-domination number

Online: 15 July 2016 (09:50:33 CEST)

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The problem of quantifying the vulnerability of graphs has received much attention nowadays, especially in the field of computer or communication networks. In a communication network, the vulnerability measures the resistance of the network to disruption of operation after the failure of certain stations or communication links. If we think of a graph as modeling a network, the average lower 2-domination number of a graph is a measure of the graph vulnerability and it is defined by

γ_{2 a v} (G) = \frac{1}{| V (G) |} \sum_{v \in V (G)} γ_{2 v} (G)

, where the lower 2-domination number, denoted by

γ_{2 v} (G)

, of the graph G relative to v is the minimum cardinality of 2-domination set in G that contains the vertex v. In this paper, the average lower 2-domination number of wheels and some related networks namely gear graph, friendship graph, helm graph and sun flower graph are calculated. Then, we offer an algorithm for computing the 2-domination number and the average lower 2-domination number of any graph G.

Preprint ARTICLE | doi:10.20944/preprints201805.0178.v1

Graph Coloring: A Novel Heuristic Based on Trailing Path; Properties, Perspective and Applications in Structured Networks

Abhirup Bandyopadhyay, Amit Kumar Dhar, Sankar Basu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: chromatic number; graph partitioning; NP to P; motif identifier; protein design

Online: 11 May 2018 (08:58:35 CEST)

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Graph coloring is a manifestation of graph partitioning, wherein, a graph is partitioned based on the adjacency of its elements. Partitioning serves potentially as a compartmentalization for any structural problem. Vertex coloring is the heart of the problem which is to find the chromatic number of a graph. The fact that there is no general efficient solution to this problem that may work unequivocally for all graphs opens up the realistic scope for combinatorial optimization algorithms to be invoked. The algorithmic complexity of graph coloring is non-deterministic in polynomial time (NP) and hard. To the best of our knowledge, there is no algorithm as yet that procures an exact solution of the chromatic number comprehensively for any and all graphs within the polynomial (P) time domain. However, several heuristics as well as some approximation algorithms have been attempted to obtain an approximate solution for the same. Here, we present a novel heuristic, namely, the 'trailing path', which returns an approximate solution of the chromatic number within polynomial time, and, with a better accuracy than most existing algorithms. The ‘trailing path’ algorithm is effectively a subtle combination of the search patterns of two existing heuristics (DSATUR and Largest First), and, operates along a trailing path of consecutively connected nodes (and thereby effectively maps to the problem of finding spanning tree(s) of the graph) during the entire course of coloring, where essentially lies both the novelty and the apt of the current approach. The study also suggests that the judicious implementation of randomness is one of the keys towards rendering an improved accuracy in such combinatorial optimization algorithms. Apart from the algorithmic attributes, essential properties of graph partitioning in random and different structured networks have also been surveyed, followed by a comparative study. The study reveals the remarkable stability and absorptive property of chromatic number across a wide array of graphs. Finally, a case study is presented to demonstrate the potential use of graph coloring in protein design – yet another hard problem in structural and evolutionary biology.

Preprint ARTICLE | doi:10.20944/preprints202301.0463.v1

Trainable Activations for Image Classification

Evgenii Pishchik

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Trainable Activations, Trainable Activation Functions, CosLU, DELU, LinComb, NormLinComb, ReLUN, ScaledSoftSign, ShiLU

Online: 26 January 2023 (02:59:29 CET)

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Preprint ARTICLE | doi:10.20944/preprints201707.0017.v1

Quasirecognition by Prime Graph of the Groups ²D_2n(q) Where q < 10⁵

Hossein Moradi, Mohammad Reza Darafsheh, Ali Iranmanesh

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: prime graph; simple group; orthogonal groups; quasirecognition

Online: 10 July 2017 (09:01:04 CEST)

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Preprint ESSAY | doi:10.20944/preprints201711.0063.v1

Multi-Scale Deep Neural Network for Mitosis Detection in Breast Cancer Histological Images

Boqian Wu, Binwen Fan, Qiao Xiao, Tasleem Kausar, Wenfeng Wang

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: breast cancer; mitosis detection; CNN; Stain-normalization; CRF; multi-scale feature

Online: 9 November 2017 (10:05:53 CET)

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Preprint ARTICLE | doi:10.20944/preprints202103.0337.v1

Drug Target Prediction Using Graph Representation Learning via Substructures Contrast

Shicheng Cheng, Liang Zhang, Bo Jin, Qiang Zhang, Xinjiang Lu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Graph embedding; Link prediction; Mutual information; Subgraph

Online: 12 March 2021 (08:47:29 CET)

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Preprint ARTICLE | doi:10.20944/preprints201811.0530.v2

Digital Image Segmentation in Matlab: A Brief Study on Otsu’s Image Thresholding

Md. Abu Bakr Siddique, Rezoana Bente Arif, Mohammad Mahmudur Rahman Khan

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Image segmentation, Otsu’s thresholding, Two level thresholding, Three level thresholding, Error minimization, Bayes decision, Probability density function (PDF).

Online: 5 February 2019 (08:12:08 CET)

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Preprint REVIEW | doi:10.20944/preprints202104.0734.v1

Code-based Post-Quantum Cryptography

Chithralekha Balamurugan, Kalpana Singh, Ganeshvani Ganesan, Muttukrishnan Rajarajan

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Quantum computing; Post-quantum cryptography; Code-based cryptography; cryptosystem; cryptography; Privacy

Online: 28 April 2021 (08:51:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201902.0105.v1

A Novel Interactive Fusion Method with Images and Point Clouds for 3D Object Detection

Kai Xu, Zhile Yang, Yangjie Xu, Liangbing Feng

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: fusion; point clouds; images; object detection

Online: 12 February 2019 (16:53:19 CET)

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Preprint ARTICLE | doi:10.20944/preprints201705.0028.v1

An Automatic Measurement Method for Absolute Depth of Objects in Two Monocular Images Based on SIFT Feature

Lixin He, Jing Yang, Bin Kong, Can Wang

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: monocular image; image segment; SIFT; depth measurement; convex hull

Online: 3 May 2017 (09:19:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201902.0252.v1

A Secure and Optimal Method of Steganography Using Bit Combination and Dynamical Rotation over Addresses

Moses Okello

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: General Mathematics, Combinatorial, Algebra, Steganography, Probability, Cryptography

Online: 27 February 2019 (11:47:18 CET)

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Preprint ARTICLE | doi:10.20944/preprints201710.0018.v1

Challenges and Opportunities for Visualization and Analysis of Graph-Modeled Medical Data

Giuseppe Agapito, Pietro Hiram Guzzi, Mario Cannataro

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Biological Network; Graphs; Statistical Analysis

Online: 3 October 2017 (16:52:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202202.0007.v1

Natural Language Processing Of Helpline Chat Data Before And During The Pandemic Revealed Significant Decrease In Self-image Appreciation And Changes In Other Traits

Maria Paz Raveau, Julian Goñi, José Rodriguez, Isidora Paiva, Fernanda Barriga, Maria Paz Hermosilla, Claudio Fuentes, Susana Eyheramendy

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: mental health; natural language processing; interdisciplinary research; mental health helpline

Online: 1 February 2022 (12:03:47 CET)

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Preprint ARTICLE | doi:10.20944/preprints201805.0012.v1

Layered Graphs: A Class that Admits Polynomial Time Solutions for Some Hard Problems

Bhadrachalam Chitturi, Srijith Balachander, Sandeep Satheesh, Krithic Puthiyoppil

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: NP-complete; graph theory; layered graph; polynomial time; quasi-polynomial time; dynamic programming; independent set; vertex cover; dominating set

Online: 2 May 2018 (05:41:54 CEST)

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The independent set, IS, on a graph

G = (V, E)

is

V^{*} \subseteq V

such that no two vertices in

V^{*}

have an edge between them. The MIS problem on G seeks to identify an IS with maximum cardinality, i.e. MIS.

V^{*} \subseteq V

is a vertex cover, i.e. VC of

G = (V, E)

if every

e \in E

is incident upon at least one vertex in

V^{*}

.

V^{*} \subseteq V

is dominating set, DS, of

G = (V, E)

if

\forall v \in V

either

v \in V^{*}

or

\exists u \in V^{*}

and

(u, v) \in E

. The MVC problem on G seeks to identify a vertex cover with minimum cardinality, i.e. MVC. Likewise, MCV seeks a connected vertex cover, i.e. VC which forms one component in G, with minimum cardinality, i.e. MCV. A connected DS, CDS, is a DS that forms a connected component in G. The problems MDS and MCD seek to identify a DS and a connected DS i.e. CDS respectively with minimum cardinalities. MIS, MVC, MDS, MCV and MCD on a general graph are known to be NP-complete. Polynomial time algorithms are known for bipartite graphs, chordal graphs, cycle graphs, comparability graphs, claw-free graphs, interval graphs and circular arc graphs for some of these problems. We introduce a novel graph class, layered graph, where each layer refers to a subgraph containing at most some k vertices. Inter layer edges are restricted to the vertices in adjacent layers. We show that if

k = Θ (log ∣ V ∣)

then MIS, MVC and MDS can be computed in polynomial time and if

k = O ({(log ∣ V ∣)}^{α})

, where

α < 1

, then MCV and MCD can be computed in polynomial time. If

k = Θ ({(log ∣ V ∣)}^{1 + ϵ})

, for

ϵ > 0

, then MIS, MVC and MDS require quasi-polynomial time. If

k = Θ (log ∣ V ∣)

then MCV, MCD require quasi-polynomial time. Layered graphs do have constraints such as bipartiteness, planarity and acyclicity.

Working Paper ARTICLE

A Comparative Analysis of Image Denoising Problem: Noise Models, Denoising Filters and Applications

Subrato Bharati, Tanvir Zaman Khan, Prajoy Podder, Nguyen Quoc Hung

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Gaussian noise; Speckle Noise; Mean square error(MSE); DE noising filters; Maximum difference value (MD); Peak signal to noise ratio(PSNR)

Online: 4 June 2020 (05:52:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0467.v1

A Polynomial Time Algorithm for Graph Isomorphism and Automorphism

Sardar Anisul Haque

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: graph isomorphism; graph automorphism; polynomial time algorithm

Online: 24 August 2021 (13:56:35 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201712.0025.v1

Collective List-only Entity Linking: A Graph-based Approach

Weixin Zeng, Xiang Zhao, Jiuyang Tang

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: list-only entity linking; named entity disambiguation; graph-based approach

Online: 4 December 2017 (16:01:32 CET)

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Preprint ARTICLE | doi:10.20944/preprints201711.0053.v3

Estimating Full Regional Skeletal Muscle Fibre Orientation from B-Mode Ultrasound Images Using Convolutional, Residual, and Deconvolutional Neural Networks

Ryan Cunnigham, María B Sánchez, Greg May, Ian Loram

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: ultrasound; b-mode; skeletal muscle; fascicle orientation; pennation angle; fiber orientation; fiber tract; fascicle tract; convolutional neural network; deconvolutional neural network

Online: 19 January 2018 (14:05:16 CET)

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Preprint ARTICLE | doi:10.20944/preprints201803.0128.v1

Orthogonal Moment Extraction and Classification of Melanoma Images

Sudhakar Singh, Shabana Urooj

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: moments invariants; ZM,PZM; OFMM; SVM; PSO

Online: 16 March 2018 (05:26:31 CET)

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Preprint ARTICLE | doi:10.20944/preprints202003.0313.v1

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

Jakaria Rabbi, Nilanjan Ray, Matthias Schubert, Subir Chowdhury, Dennis Chao

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Object detection; faster region-based convolutional neural network (FRCNN); single-shot multi-box detector (SSD); super resolution; remote sensing imagery; edge enhancement

Online: 20 March 2020 (09:50:54 CET)

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Preprint REVIEW | doi:10.20944/preprints202108.0155.v1

A Comprehensive Survey of Cognitive Graphs: Techniques, Applications, Challenges

Meiling Chen, Ye Tian, Zhaorui Wang, Hong Xu, Bo Jiang

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Cognitive Graph; Knowledge Graph; Knowledge Reasoning; Natural Language Generating

Online: 6 August 2021 (10:14:00 CEST)

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Preprint REVIEW | doi:10.20944/preprints202104.0199.v1

A Survey of RDF Stores & SPARQL Engines for Querying Knowledge Graphs

Waqas Ali, Muhammad Saleem, Yao Bin, Aidan Hogan, A.-C. Ngonga Ngomo

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Knowledge Graph; ·Storage·Indexing; ·Query Processing; ·SPARQL; ·Benchmarks

Online: 7 April 2021 (11:50:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201905.0262.v1

Using Difference Scheme Method to the Fractional Telegraph Model with Atangana-Baleanu-Caputo Derivative

Mahmut Modanli

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: fractional telegraph model with Atangana-Baleanu derivative; Laplace method; stability inequalites; difference schemes; implicit finite method

Online: 21 May 2019 (11:43:12 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201903.0086.v1

Spatio-Temporal Image Representation of 3D Skeletal Movements for View-Invariant Action Recognition with Deep Convolutional Neural Networks

Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio A. Velastin

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: 3D human action recognition; skeleton-based representation; SPMF; enhanced-SPMF; AHE; D-CNNs; DenseNet

Online: 7 March 2019 (09:10:43 CET)

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Preprint ARTICLE | doi:10.20944/preprints201805.0126.v1

A Zero-Knowledge Proof Based on a Multivariate Polynomial Reduction of the Graph Isomorphism Problem

Edgar González Fernández, Guillermo Morales-Luna, Feliú Sagols Troncoso

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: graph isomorphism problem; multivariate polynomial system; zero-knowledge proof

Online: 8 May 2018 (09:35:15 CEST)

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Preprint REVIEW | doi:10.20944/preprints202008.0215.v2

Deep Learning Driven Automated Detection of COVID-19 from Radiography Images: A Comparative Analysis

Sejuti Rahman, Sujan Sarker, Abdullah Al Miraj, Ragib Amin Nihal, A. K. M. Nadimul Haque, Abdullah Al Noman

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: COVID-19; deep learning; radiography; automated detection; medical imaging; SARS-CoV-2

Online: 19 October 2020 (10:49:25 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201907.0298.v1

Securing IoT Based RFID Systems: A Robust Authentication Protocol Using Symmetric Cryptography

Khwaja Mansoor, Anwar Ghani, Shehzad Ashraf Chaudhry, Shahaboddin Shamshirband, Shahbaz Ahmed Khan Ghayyur, Ely Salwana

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: authentication protocol; IoT Security; RFID security; symmetric cryptography

Online: 26 July 2019 (04:30:32 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202101.0579.v1

Interpreting and Comparing Convolutional Neural Networks: A Quantitative Approach

Mohammad Mohaiminul Islam, Zahid Hassan Tushar

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Network Interpretation; Image Classification; Convolutional Neural Network; Integrated Gradient

Online: 28 January 2021 (12:29:20 CET)

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Preprint ARTICLE | doi:10.20944/preprints202002.0231.v1

Stochastic Activation Function Layers for Convolutional Neural Networks

Loris Nanni, Alessandra Lumini, Stefano Ghidoni, Gianluca Maguolo

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Convolutional Neural Networks; ensemble of classifiers; activation functions; image classification; skin detection

Online: 17 February 2020 (01:50:08 CET)

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Preprint ARTICLE | doi:10.20944/preprints202208.0350.v1

Covid-19 Vaccination and Mental Stress within Diverse Socio-demographic Groups

Wasiq Khan, Bilal M. Khan, Salwa Yasen, Ahmed Al-Dahiri, Dhiya Al-Jumeily, Abir Hussain

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Mental stress Covid-19; Covid-19 vaccine dataset; Vaccine sociodemographic; Vaccine acceptance rate; Vaccine perception

Online: 18 August 2022 (13:36:16 CEST)

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Preprint REVIEW | doi:10.20944/preprints202205.0343.v1

A Comprehensive Survey of Depth Completion Approaches

Muhammad Ahmed Ullah Khan, Danish Nazir, Alain Pagani, Hamam Mokayed, Marcus Liwicki, Didier Stricker, Muhammad Zeshan Afzal

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Depth Completion; Depth Maps; Image-Guidance; Lidar

Online: 25 May 2022 (05:26:16 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202005.0052.v1

Social-Group-Optimization Assisted Kapur’s Entropy and Morphological Segmentation for Automated Detection of COVID-19 Infection from Computed Tomography Images

Nilanjan Dey, V. Rajinikant, Simon James Fong, M. Shamim Kaiser, Mufti Mahmud

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: COVID-19 infection; CT scan image; serial feature fusion; KNN classiﬁer; segmentation; detection accuracy

Online: 5 May 2020 (02:32:05 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201805.0302.v1

Relating Vertex and Global Graph Entropy in Randomly Generated Graphs

Philip Tee, George Parisis, Luc Berthouze, Ian Wakeman

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: graph entropy; chromatic classes; random graphs

Online: 22 May 2018 (11:59:26 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202009.0302.v1

Lightweight Cryptographic Algorithms on Resource-Constrained Devices

Thomas Xuan Meng, William Buchanan

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Lightweight cryptography; Internet of Thing (IoT); Resource constrained devices; Encryption-decryption; Symmetric cipher; Asymmetric cipher; Speed; Efficiency; Security; Cost; Raspberry Pi

Online: 13 September 2020 (23:50:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0202.v1

A Graph Database Model for Knowledge Extracted from Place Descriptions

Hao Chen, Maria Vasardani, Stephan Winter, Martin Tomko

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: place; spatial property graph; place graph; graph database; place description

Online: 16 April 2018 (10:05:25 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201807.0381.v1

The Double Roman Domination Numbers of Generalized Petersen Graphs P(n, 2)

Huiqin Jiang, Pu Wu, Zehui Shao, Jia-Bao Liu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: double Roman domination; discharging approach; generalized Petersen graphs

Online: 20 July 2018 (11:59:01 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202005.0493.v1

Diabetic Retinopathy Diagnostics from Retinal Images based on Deep Convolutional Networks

G. Arun Sampaul Thomas, Y. Harold Robinson, E. Golden Julie, Vimal Shanmuganathan, Yunyoung Nam, Seungmin Rho

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Convolutional Neural Networks; Dental Diagnosis; Image Recognition; Diabetic Retinopathy detection

Online: 31 May 2020 (18:55:43 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201912.0089.v1

A Study on the Detection of Cattle in UAV Images Using Deep Learning

Jayme Garcia Arnal Barbedo, Luciano Vieira Koenigkan, Thiago Teixeira Santos, Patrícia Menezes Santos

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: unmanned aerial vehicles; drones; Canchim breed; Nelore breed; convolutional neural networks

Online: 7 December 2019 (01:37:17 CET)

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Preprint ARTICLE | doi:10.20944/preprints201901.0025.v1

Nikfar Domination in Neutrosophic Graphs

Mohammadesmail Nikfar

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Neutrosophic graph, bridge, tree, eective edge, nikfar domination.

Online: 3 January 2019 (13:46:43 CET)

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Preprint ARTICLE | doi:10.20944/preprints201905.0308.v1

Comparing Yiq and Ycbcr Colour Image Transforms for Semi-Fragile Medical Image Steganography

Peter Eze, Parampalli Udaya, Robin Evans, Dongxi Liu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Colour Model; Steganography; Medical Image; C4S; distortion

Online: 27 May 2019 (10:13:02 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201912.0059.v1

Classification of Hyperspectral Image Based on Double-Branch Dual-Attention Mechanism Network

Li Rui

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: hyperspectral image classiﬁcation; spectral-spatial feature fusion; channel-wise attention; spatial-wise attention

Online: 5 December 2019 (04:05:48 CET)

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Preprint ARTICLE | doi:10.20944/preprints201711.0053.v1

Estimating Full Regional Skeletal Muscle Fibre Curvature from b-Mode Ultrasound Images Using Convolutional-Deconvolutional Neural Networks

Ryan Cunnigham, María B Sánchez, Greg May, Ian Loram

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: ultrasound; b-mode; skeletal muscle; fascicle orientation; pennation angle; fiber orientation; fiber tract; fascicle tract; convolutional neural network; deconvolutional neural network

Online: 8 November 2017 (04:36:50 CET)

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Preprint ARTICLE | doi:10.20944/preprints201811.0530.v1

Digital Image Segmentation in Matlab: A Brief Study on Otsu’s Image Thresholding

Md. Abu Bakr Siddique, Rezoana Bente Arif, Mohammad Mahmudur Rahman Khan

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Image segmentation, Otsu’s thresholding, Two level thresholding, Three level thresholding, Error minimization, Bayes decision, Probability density function (PDF).

Online: 21 November 2018 (15:51:51 CET)

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Preprint ARTICLE | doi:10.20944/preprints202105.0468.v1

3D Reconstruction Method of Rapeseed Plants in the Whole Growth Period Using RGB-D Camera

Xiaowen Teng, Guangsheng Zhou, Yuxuan Wu, Chenglong Huang, Wanjing Dong, Shengyong Xu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: 3D reconstruction; ICP; Azure Kinect; RGB-D image processing; point cloud filtering; rapeseed

Online: 20 May 2021 (09:52:14 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201711.0053.v2

Estimating Full Regional Skeletal Muscle Fibre Curvature from b-Mode Ultrasound Images Using Convolutional-Deconvolutional Neural Networks

Ryan Cunnigham, María B Sánchez, Greg May, Ian Loram

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: ultrasound; b-mode; skeletal muscle; fascicle orientation; pennation angle; fiber orientation; fiber tract; fascicle tract; convolutional neural network; deconvolutional neural network

Online: 16 November 2017 (04:34:20 CET)

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Preprint ARTICLE | doi:10.20944/preprints201811.0252.v1

BAGAN: Effective Data Generation Based on GAN Augmented 3D Synthesizing

Yan Ma, Kang Liu, Zhi-Bin Guan, Xin-Kai Xu, Xu Qian, Hong Bao

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: object recognition; image data synthesizing; Human-computer interaction; data synthesizing for immersive HCI; generative adversarial nets; BAGAN

Online: 9 November 2018 (16:00:39 CET)

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Preprint ARTICLE | doi:10.20944/preprints201901.0024.v1

Nikfar Domination in Fuzzy Graphs

Mohammadesmail Nikfar

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: fuzzy graph, fuzzy bridge, -strong edge, nikfar domination, dynamic networks

Online: 3 January 2019 (13:43:25 CET)

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Preprint ARTICLE | doi:10.20944/preprints202201.0090.v1

DeHyFoNet: Deformable Hybrid Network for Formula Detection in Scanned Document Images

Muhammad Zeshan Afzal, Khurram Azeem Hashmi, Alain Pagani, Marcus Liwicki, Didier Stricker

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: formula detection; Hybrid Task Cascade network; mathematical expression detection; document image analysis; deep neural networks; computer vision

Online: 6 January 2022 (12:56:23 CET)

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Preprint ARTICLE | doi:10.20944/preprints201808.0007.v1

Vertex Labeling and Routing for Farey-Type Symmetrically-Structured Graphs

Wenchao Jiang, Yinhu Zhai, Zhigang Zhuang, Paul Martin, Zhiming Zhao, Jia-Bao Liu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: complex networks; deterministic models; Farey-type graphs; vertex labeling; shortest path routing

Online: 1 August 2018 (08:36:16 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201909.0298.v1

Undirected Graphs: Is the Shift-Enabled Condition Trivial or Necessary?

Liyan Chen, Samuel Cheng, Kanghang He, Lina Stankovic, Vladimir Stankovic

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: graph signal processing; shift-enabled graphs; shift-invariant filter; undirected graph

Online: 26 September 2019 (11:03:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.0050.v1

Object Detection in Adverse Weather for Autonomous Driving Through Data Merging and YOLOv8

Debasis Kumar, Naveed Muhammad

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Autonomous Driving; Harsh Weather; Object Detection; Data Merging; Deep Neural Networks; YOLOv8

Online: 1 September 2023 (09:57:21 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201806.0456.v1

Graphs and Binary Systems

Hee Sik Kim, J. Neggers, Sun Shin Ahn

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: binary system(groupoid); minimum (mutual) covering set; (mutual) shortest distance; (di)frame graph; d/BCK-algebra

Online: 28 June 2018 (04:48:32 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201805.0243.v3

Non-Destructive System Based on Electrical Tomography and Machine Learning to Analyze Moisture of Buildings

Tomasz Rymarczyk, Grzegorz Kłosowski, Edward Kozłowski

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: inverse problem; electrical tomography; moisture inspection; dampness analysis; machine learning; nondestructive evaluation

Online: 5 July 2018 (08:17:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201810.0490.v1

Investigation of Disintegration and Dissolution Behavior of Mefenamic Acid Drug Formulation Using Numeric Solution of Noyes-Whitney Equation with Cellular Automata Model on Microtomographic Surfaces and Rational Arrangements of Tablet Components

Reiji Yokoyama, Go Kimura, Christian Schlepütz, Jörg Huwyler, Maxim Puchkov

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: drug release simulation; disintegration simulation; poorly water soluble drug; mefenamic acid; Noyes-Whitney equation; cellular automata; synchrotron microtomography

Online: 22 October 2018 (11:38:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0085.v2

The Results on Vertex Domination in Fuzzy Graphs

Mohammadesmail Nikfar

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: fuzzy graph; $\alpha$-strong arcs; weight of nodes; vertex domination

Online: 29 April 2019 (12:34:08 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201806.0051.v1

Bounds for General Connectivity Indices of Tensor Product of Connected Graphs

Shakila Baby, Muhammad Kashif Shafiq, Asim Naseem, Hafiz Muhammad Afzal Siddiqui

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: tensor product of graphs; Randić index; sum-connectivity index; harmonic index

Online: 5 June 2018 (08:02:41 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201805.0243.v1

Non-Destructive System Based on Electrical Tomography and Machine Learning to Analyze Moisture of Buildings

Tomasz Rymarczyk, Grzegorz Kłosowski, Edward Kozłowski

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: inverse problem; electrical tomography; moisture inspection; dampness analysis; machine learning, nondestructive evaluation

Online: 17 May 2018 (11:33:13 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0389.v1

Comparison of Modern Cryptography Methods

Amandip Dutta

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: cryptography, elgamal, rsa, ecc, blowfish, encryption, decryption

Online: 26 July 2022 (06:03:09 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202105.0176.v1

A Graphical Based Video Steganography

Samir Bandyopadhyay, Payal Bose, Vishal Goyel

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Video Steganography, Least Significant Bit (LSB) Coding, Double key Encryption, Decryption, Password Verification, Signature Verification

Online: 10 May 2021 (11:21:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0085.v3

Vertex Domination in Fuzzy Graphs

Mohammadesmail Nikfar

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: fuzzy graph; fuzzy bridge; fuzzy tree; $\alpha$-strong arc; vertex domination

Online: 5 May 2019 (12:20:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201906.0248.v1

Gray Level Image Threshold Using Neutrosophic Shannon Entropy

Vasile Patrascu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: image segmentation; neutrosophic information; Shannon entropy; gray level image threshold

Online: 25 June 2019 (08:48:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201910.0319.v1

Using Convolutional Networks and Satellite Imagery to Predict Disease Density in a Developing Country

Rahman Sanya, Gilbert Maiga, Ernest Mwebaze

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: convolutional networks; satellite imagery; predictive modeling; disease density; urban housing; developing country

Online: 28 October 2019 (11:41:25 CET)

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Preprint ARTICLE | doi:10.20944/preprints202003.0313.v3

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

Jakaria Rabbi, Nilanjan Ray, Matthias Schubert, Subir Chowdhury, Dennis Chao

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: object detection; faster region-based convolutional neural network (FRCNN); single-shot multibox detector (SSD); super-resolution; remote sensing imagery; edge enhancement; satellites

Online: 29 April 2020 (13:33:56 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202201.0457.v1

Investigating Transfer Learning in Graph Neural Networks

Nishai Kooverjee, Steven James, Terence Van Zyl

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: graph neural networks; machine learning; transfer learning; multi-task learning

Online: 31 January 2022 (12:49:31 CET)

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Working Paper ARTICLE

Hierarchical Pooling in Graph Neural Networks to Enhance Classification Performance in Large Datasets

Hai Van Pham, Dat Hoang Thanh, Philip Moore

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Knowledge graphs; hierarchical pooling; graph classification; graph neural networks; FPool; large graph sensor datasets

Online: 15 June 2021 (14:32:53 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202109.0059.v1

CasTabDetectoRS: Cascade Network for Table Detection in Document Images with Recursive Feature Pyramid and Switchable Atrous Convolution

Khurram Azeem Hashmi, Alain Pagani, Marcus Liwicki, Didier Stricker, Muhammad Zeshan Afzal

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: table detection; table recognition; cascade Mask R-CNN; atrous convolution; recursive feature pyramid networks; document image analysis; deep neural networks; computer vision, object detection.

Online: 3 September 2021 (11:05:10 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202008.0336.v1

Classification of Amber Gemstone Objects by Shape

Armantas Ostreika, Marius Pivoras, Alfonsas Misevičius, Tomas Skersys, Linas Paulauskas

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: image processing; image classification; computer vision; expert systems; amber gemstones

Online: 15 August 2020 (04:39:11 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0437.v1

Graph Coverings for Investigating Non Local Structures in Proteins, Music and Poems

Michel Planat, Raymond Aschheim, Marcelo M Amaral, Fang Fang, Klee Irwin

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: mathematical poetry; musical forms; protein foldings; graph coverings

Online: 23 August 2021 (12:31:35 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0085.v1

The Results on Vertex Domination in Fuzzy Graphs

Mohammadesmail Nikfar

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: fuzzy graph; α-strong arcs; weight of nodes; vertex domination

Online: 8 April 2018 (08:24:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202106.0323.v1

New Graph Of Graph

Henry Garrett

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Regular Graph; Vertex; Degree; Numbers

Online: 11 June 2021 (14:25:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0579.v1

Space: The Re-visioning Frontier of Biological Image Analysis with Graph Theory, Computational Geometry, and Spatial Statistics

John R Jungck, Michael J Pelsmajer, Camron Chappel, Dylan Taylor

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Graph Theory; Computational Geometry; Spatial Statistics; Image analysis; Tessellations; Voronoi Polygons; Delaunay Triangulations; Minimal Spanning Trees; Pitteway Violations

Online: 31 August 2021 (15:58:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202203.0140.v1

Convolutional LSTM Approach for Left Ventricle Segmentation and Estimation of Left Ventricle Ejection Fraction in Echocardiography

Jin Gyo Jeong, DongHyun Kim, Young Jae Kim, Kyungmin Yoo, Kyungeun Ha, Wook-Jin Chung, Kwang Gi Kim

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Left ventricular ejection fraction; Left ventricle segmentation; Convolutional long short-term memory; Echocardiography

Online: 10 March 2022 (04:19:30 CET)

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Preprint ARTICLE | doi:10.20944/preprints202103.0754.v1

Augmenting Paraphrase Generation with Syntax Information using Graph Convolutional Networks

Xiaoqiang Chi, Yang Xiang

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: paraphrase generation; syntax information; Graph Convolutional Network; sequence-to-sequence

Online: 31 March 2021 (07:57:56 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202107.0262.v2

Generating the Triangulations of the Torus with the Vertex-Labeled Complete 4-Partite Graph K_{2,2,2,2}

Serge Lawrencenko, Abdulkarim Magomedov

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: group action; orbit decomposition; polynomial; graph; tree; triangulation; torus; automorphism; quaternion group

Online: 29 July 2021 (17:19:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201901.0024.v2

Nikfar Domination in Fuzzy Graphs

Mohammadesmail Nikfar

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: fuzzy graph, fuzzy bridge, α-strong edge, nikfar domination, dynamic networks.

Online: 7 May 2019 (10:14:31 CEST)

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The aim of this expository article is to present recent developments in the centuries-old discussion on the interrelations between several types of domination in graphs. However, the novelty even more prominent in the newly discovered simplified presentations of several older results. The main part of this article, concerning a new domination and older one, is presented in a narrative that answers two classical questions: (i) To what extend must closing set be dominating? (ii) How strong is the assumption of domination of a closing set? In a addition, we give an overview of the results concerning domination. The problem asks how small can a subset of vertices be and contain no edges or, more generally how can small a subset of vertices be and contain other ones. Our work was as elegant as it was unexpected being a departure from the tried and true methods of this theory that had dominated the field for one fifth a century. This expository article covers all previous definitions. The inability of previous definitions in solving even one case of real-world problems due to the lack of simultaneous attentions to the worthy both of vertices and edges causing us to make the new one. The concept of domination in a variety of graphs models such as crisp, weighted and fuzzy, has been in a spotlight. We turn our attention to sets of vertices in a fuzzy graph that are so close to all vertices, in a variety of ways, and study minimum such sets and their cardinality. A natural way to introduce and motivate our subject is to view it as a real-world problem. In its most elementary form, we consider the problem of reducing waste of time in transport planning. Our goal here is to first describe the previous definitions and the results, and then to provide an overview of the flows ideas in their articles. The final outcome of this article is twofold: (i) Solving the problem of reducing waste of time in transport planning at static state; (ii) Solving and having a gentle discussions on problem of reducing waste of time in transport planning at dynamic state. Finally, we discuss the results concerning holding domination that are independent of fuzzy graphs. We close with a list of currently open problems related to this subject. Most of our exposition assumes only familiarity with basic linear algebra, polynomials, fuzzy graph theory and graph theory.

Preprint ARTICLE | doi:10.20944/preprints201905.0125.v1

Parkinson’s Disease Detection Using Biogeography-Based Optimization

Shahab Shahab, Somayeh Hessam, Shaghayegh Vahdat, Irvan Masoudi Asl, Mahnaz Kazemipoor, Timon Rabczuk

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Parkinson’s disease (PD); Biomedical voice measurements; Multi-layer Perceptron Neural Network (MLP); Biogeography-based Optimization (BBO); Medical diagnosis. Bio-inspired computation

Online: 10 May 2019 (13:56:59 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202108.0091.v1

Data Enhancement via Low-Rank Matrix Reconstruction in Pulsed Thermography for Carbon-fiber-Reinforced Polymers

Samira Ebrahimi, Julien R Fleuret, Matthieu Klein, Louis-Daniel Théroux, Clemente Ibarra-Castanedo, Xavier P.V. Maldague

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Robust PCA, RPCA, PCP, IALM, Noise Reduction, Pulsed Thermography, CFRP

Online: 3 August 2021 (15:26:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202104.0413.v2

Total Face Irregularity Strength of Type (Alpha, Beta, Gamma) of Grid Graphs

Abdul Aleem Mughal, Raja Noshad Jamil

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Total Face labeling of type (Alpha, Beta, Gamma); Total face irregularity strength; artesian product of path graphs; Graph Labeling; Graph theory

Online: 21 April 2021 (12:46:29 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201804.0119.v1

Vertex Domination in t-Norm Fuzzy Graphs

Mohammadesmail Nikfar

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: t-norm Fuzzy graph; t-norm; fuzzy tree; bridge; α-strong edges; vertex domination

Online: 10 April 2018 (08:41:33 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202211.0439.v1

A Comparative Study between Graph Database and Traditional Approach to forecast Coauthor Link Prediction based on Machine Learning Models

Mohammad Rezwanul Huq, Sanjeda Sara Jennifer, Shafiul Mahmud Partho, Fariha Fairuz

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: coauthorship; coauthorship Network; Link Prediction; Graph Database; Nodes

Online: 23 November 2022 (07:38:22 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0139.v1

Segmentation Uncertainty Estimation as a Sanity Check for Image Biomarker Studies

Ivan Zhovannik, Dennis Bontempi, Alessio Romita, Elisabeth Pfaehler, Sergey Primakov, Andre Dekker, Johan Bussink, Alberto Traverso, René Monshouwer

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: uncertainty; prognostic modeling; image biomarkers; radiomics; radiomics harmonization

Online: 9 February 2022 (11:50:10 CET)

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Problem. Image biomarker analysis, also known as radiomics, is a tool for tissue characterization and treatment prognosis that relies on routinely acquired clinical images and delineations. Due to the uncertainty in image acquisition, processing, and segmentation (delineation) protocols, radiomics often lacks reproducibility. Radiomics harmonization techniques have been proposed as a solution to reduce these sources of uncertainty and/or their influence on the prognostic model performance. A relevant question is how to estimate the protocol-induced uncertainty of a specific image biomarker, what the effect is on the model performance, and how to optimize the model given the uncertainty. In this manuscript, we show how protocol uncertainty can drastically reduce prognostic model performance. We introduce an effect-size measure η that assesses the protocol-induced uncertainty versus the measurable effect. Methods. Two non-small cell lung cancer (NSCLC) cohorts, composed of 421 and 240 patients respectively, were used for training and testing. Per patient, a Monte Carlo algorithm was used to generate three hundred synthetic contours with a surface dice tolerance measure less than 1.18 mm with respect to the original GTV. These contours were subsequently used to derive 104 radiomic features, which were ranked on their relative sensitivity to contour perturbation, expressed in the parameter η. The top four (low η) and the bottom four (high η) features were selected for two models based on Cox proportional hazards model. To investigate the influence of segmentation uncertainty on the prognostic model, we trained and tested the setup in 5000 augmented realizations (using a Monte Carlo sampling method); the log-rank test was used to assess the stratification performance and stability to segmentation uncertainty. Results. Although both low and high η setup showed significant testing set log-rank p-values (p=0.01) in the original GTV delineations (without segmentation uncertainty introduced), in the model with high uncertainty to effect ratio only around 30% of the augmented realizations resulted in model performance with p < 0.05 in the test set. In contrast, the low η setup performed with log-rank p < 0.05 in 90% of the augmented realizations. Moreover, the high η setup classification was uncertain for 50% of the subjects in the testing set (for 80% agreement rate), whereas the low η setup was uncertain only in 10% of the cases. The code and part of the data are available at https://github.com/Maastro-CDS-Imaging-Group/sure. Discussion. Estimating image biomarker model performance based only on the original GTV segmentation without considering segmentation uncertainty may be deceiving. The model might result in a significant stratification performance, but can be unstable for delineation variations, which are inherent to manual segmentation. Simulating segmentation uncertainty using the method described allows for more stable image biomarker estimation, selection, and model development. The segmentation uncertainty estimation method described here is universal and can be extended to estimate other protocol uncertainties (such as image acquisition and pre-processing).

Working Paper ARTICLE

Integrating EfficientNet into an HAFNet structure for Building Mapping in High-Resolution Optical Earth Observation Data

Luca Ferrari, Fabio Dell'Acqua, Peng Zhang, Peijun Du

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: attention mechanism; building mapping; data fusion; EfficientNet; HAFNet; high-resolution imagery (HRI); light detection and ranging (LiDAR); mapping; urban areas

Online: 19 August 2021 (08:50:20 CEST)

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Automated extraction of buildings from earth observation (EO) data is important for various applications, including updating of maps, risk assessment, urban planning, policy making. Combining data from different sensors such as high-resolution multispectral (HRI) and light detection and ranging (LiDAR) has shown great potential in building extraction. Deep learning (DL) is increasingly used in multimodal data fusion and urban object extraction. However, DL-based multimodal fusion networks may underperform due to insufficient learning of “joint features” from multiple sources and oversimplified approaches to fusing multimodal features. Recently, an hybrid attention-aware fusion network (HAFNet) has been proposed for building extraction from a dataset including co-located Very-High-Resolution (VHR) optical images and Light Detection And Ranging (LiDAR) joint data. The system reported good performances thanks to the adaptivity of the attention mechanism to the features of the information content of the three streams but suffered from model overparametrization, which inevitably leads to long training times and heavy computational load. In this paper the authors propose a restructuring of the scheme, which involved replacing VGG-16-like encoders with the recently proposed EfficientNet, whose advantages counteract exactly the issues found with the HAFNet scheme. The novel configuration was tested on multiple benchmark datasets, reporting great improvements in terms of processing times, and also in terms of accuracy. The new scheme, called HAFNetE (HAFNet with EfficientNet integration), appears indeed capable of achieving good results with less parameters, translating into better computational efficiency. Based on these findings, we can conclude that, given the current advancements in single-thread schemes, the classical multi-thread HAFNet scheme could be effectively transformed by the HAFNetE scheme by replacing VGG-16 with EfficientNet blocks on each single thread. The remarkable reduction achieved in computational requirements moves the system one step closer to on-board implementation in a possible, future “urban mapping” satellite constellation.

Preprint ARTICLE | doi:10.20944/preprints202205.0233.v1

Dynamic Texture Analysis of Water Flow Video Using Temporal Binary Patern

Bernadus Herdi Sirenden, Petrus Mursanto, Sensus Wijonarko

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: water surface velocity; image based measurement; dynamic texture analysis

Online: 17 May 2022 (14:01:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201811.0248.v1

Complexity of some of Pyramid Graphs Created from a Gear Graph

Salama Daoud, Jia-Bao Liu

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Complexity; Chebyshev Polynomials; Gear graph; Pyramid graphs.

Online: 9 November 2018 (15:17:44 CET)

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Preprint ARTICLE | doi:10.20944/preprints201805.0243.v2

Non-Destructive System Based on Electrical Tomography and Machine Learning to Analyze Moisture of Buildings

Tomasz Rymarczyk, Grzegorz Kłosowski, Edward Kozłowski

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: inverse problem; electrical tomography; moisture inspection; dampness analysis; machine learning, nondestructive evaluation

Online: 12 June 2018 (10:58:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202207.0389.v2

Comparison of Modern Cryptography Methods

Amandip Dutta

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: blowfish, cryptography, elgamal, elliptic-curve, encryption, decryption, Rivest-Shamir-Adleman

Online: 26 August 2022 (04:15:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202010.0507.v1

The Domination Entropy of The Graphs

Bünyamin Şahin

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Graph Entropy; Domination; Domination Polynomial; Information Functional

Online: 26 October 2020 (09:24:42 CET)

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Preprint REVIEW | doi:10.20944/preprints202204.0219.v1

Preliminary Landscape Analysis of Deep Tomographic Imaging Patents

Ge Wang, Qingsong Yang, Wenxiang Cong, Donna Donna

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Artificial intelligence (AI), machine learning; deep learning; medical imaging; tomography; image reconstruction

Online: 25 April 2022 (05:35:17 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202011.0511.v2

Rumor Detection Based on SAGNN: Simplified Aggregation Graph Neural Networks

Liang Zhang, Jingqun Li, Bin Zhou, Yan Jia

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: rumor detection; graph neural network; artificial intelligence

Online: 22 December 2020 (14:23:02 CET)

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Preprint ARTICLE | doi:10.20944/preprints202201.0429.v1

Global Offensive Alliance in Strong Neutrosophic Graphs

Henry Garrett

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Modified Neutrosophic Number; Global Offensive Alliance; Complete Neutrosophic Graph

Online: 28 January 2022 (08:47:20 CET)

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New setting is introduced to study the global offensive alliance. Global offensive alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global offensive alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs containing complete, empty, path, cycle, star, and wheel are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is defined in new way. It’s first time to define this type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-offensive-alliance number and minimal-global-offensive-alliance-neutrosophic number. Two different types of sets namely global-offensive alliance and minimal-global-offensive alliance are defined. Global-offensive alliance identifies the sets in general vision but minimal-global-offensive alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-offensive-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-offensive alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs is studied in the way that, the family only contains same classes of neutrosophic graphs. Three types of family of neutrosophic graphs including m-family of neutrosophic stars with common neutrosophic vertex set, m-family of odd complete graphs with common neutrosophic vertex set, and m-family of odd complete graphs with common neutrosophic vertex set are studied. The results are about minimal-global-offensive alliance, minimal-global-offensive-alliance number and its corresponded sets, minimal-global-offensive-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-offensive alliances. The connection of global-offensive-alliances with dominating set and chromatic number are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, path, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global offensive alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set. It leads us to the notion of global offensive alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

Preprint ARTICLE | doi:10.20944/preprints202003.0313.v2

Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network

Jakaria Rabbi, Nilanjan Ray, Matthias Schubert, Subir Chowdhury, Dennis Chao

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: object detection; faster region-based convolutional neural network (FRCNN); single-shot multi-box detector (SSD); super-resolution; remote sensing imagery; edge enhancement; satellites

Online: 16 April 2020 (03:08:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201812.0022.v1

An Efficient Image Retrieval Based on Fusion of Low-Level Visual Features

Atif Nazir, Kashif Nazir

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Image retrieval, color features, shape features, low-level features combination

Online: 3 December 2018 (13:33:45 CET)

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Preprint ARTICLE | doi:10.20944/preprints202112.0243.v1

Segmentation of Agricultural Parcels in Satellite Images Based on Historical Vegetation Index Data

Maria Pavlova, Valerii Timofeev, Dmitry Bocharov, Irina Kunina, Anna Smagina, Mikhail Zagarev

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: digital farming; remote sensing; land management; multispectral image processing; land cover mapping; agricultural field boundary

Online: 14 December 2021 (15:01:03 CET)

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Preprint ARTICLE | doi:10.20944/preprints202202.0058.v1

Are Deep Models Robust against Real Distortions? A Case Study on Document Image Classification

Saifullah -, Shoaib Ahmed Siddiqui, Stefan Agne, Andreas Dengel, Sheraz Ahmed

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Document Image Classification; Corruption Robustness; Robustness to Distortions; Model Robustness

Online: 3 February 2022 (15:24:28 CET)

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Preprint ARTICLE | doi:10.20944/preprints202102.0316.v1

Category-Theoretic Formulation of Model-Based Systems Architecting: The Concept-Model-Graph-View-Concept Transformation Cycle

Yaniv Mordecai, James Fairbanks, Edward Crawley

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Model-Based Systems Engineering; Category Theory; Object-Process Methodology; Model Analytics; Concept-Model-Graph-View-Concept; Graph Data Structures; Graph Query; Decision Support Matrix; Matrix-Based Analysis

Online: 15 February 2021 (15:44:57 CET)

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Preprint ARTICLE | doi:10.20944/preprints202305.2180.v1

Deep Camera-Radar Fusion with Attention Framework for Autonomous Vehicle Vision in Foggy Weather Conditions

Isaac Oluwadunsin Ogunrinde, Shonda Bernadin

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Sensor fusion; object detection; deep learning; autonomous vehicles; camera-radar; adverse weather; fog; attention module

Online: 31 May 2023 (07:25:27 CEST)

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Computer Science and Mathematics