Review
Version 2
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Convolutional Neural Network (CNN). A Comprehensive Overview
Version 1
: Received: 16 August 2022 / Approved: 17 August 2022 / Online: 17 August 2022 (09:46:56 CEST)
Version 2 : Received: 17 August 2022 / Approved: 18 August 2022 / Online: 18 August 2022 (03:46:35 CEST)
Version 3 : Received: 18 August 2022 / Approved: 18 August 2022 / Online: 18 August 2022 (07:39:33 CEST)
Version 2 : Received: 17 August 2022 / Approved: 18 August 2022 / Online: 18 August 2022 (03:46:35 CEST)
Version 3 : Received: 18 August 2022 / Approved: 18 August 2022 / Online: 18 August 2022 (07:39:33 CEST)
How to cite: Upreti, A. Convolutional Neural Network (CNN). A Comprehensive Overview. Preprints 2022, 2022080313. https://doi.org/10.20944/preprints202208.0313.v2 Upreti, A. Convolutional Neural Network (CNN). A Comprehensive Overview. Preprints 2022, 2022080313. https://doi.org/10.20944/preprints202208.0313.v2
Abstract
Convolutional neural network (CNN), a class of artificial neural network (ANN) is attracting interests of researchers in all research domain. CNN was invented for computer vision. They have also shown to be useful for semantic parsing, sentence modeling and other natural language processing related tasks. Here in this paper we discuss the basics of CNN models and their scope to provide a reference/baseline to the researchers interested in using CNN models in their research.
Keywords
Convolutional Neural Network; domain; natural language processing; computer vision; semantic parsing
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Commenter: Anjeel Upreti
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