Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

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)

How to cite: Upreti, A. Convolutional Neural Network (CNN). A Comprehensive Overview. Preprints 2022, 2022080313 (doi: 10.20944/preprints202208.0313.v1). Upreti, A. Convolutional Neural Network (CNN). A Comprehensive Overview. Preprints 2022, 2022080313 (doi: 10.20944/preprints202208.0313.v1).

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

MATHEMATICS & COMPUTER SCIENCE, Artificial Intelligence & Robotics

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