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Article

Deep CNN for Classification of Image Contents

Authors:

Hoon KangAuthors Info & Claims

IPMV '21: Proceedings of the 2021 3rd International Conference on Image Processing and Machine Vision

Pages 60 - 65

https://doi.org/10.1145/3469951.3469962

Published: 21 August 2021 Publication History

Abstract

In recent years the classification of images has made great progress and has been used in many fields. However, it may not be possible to classify images perfectly through the CNN because of overfitting and gradient vanishing. Most existing CNNs have too many parameters, as a result, it will take a long time to train the CNN and then to classify images. In this paper, an improved CNN, with fewer parameters, can perfectly solve the problems such as overfitting, gradient vanishing was developed. The number of designed CNN's parameters is 13M, less than that of other CNNs. In order to check the performance of the designed CNN, the database such as MNIST and CIFAR-10 were used to test the CNNs. The test result was 99.467% and 91.167% respectively. These results are similar to test accuracy of other existing CNNs. Therefore, it was confirmed that the designed CNN not only has fewer parameters than the other CNNs but also shows high test accuracy.

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Cited By

Komiya DAkiyoshi M(2023)A Classification Method for “Kawaii” Images Using Four Feature FiltersDistributed Computing and Artificial Intelligence, 20th International Conference10.1007/978-3-031-38333-5_30(296-305)Online publication date: 21-Jul-2023
https://doi.org/10.1007/978-3-031-38333-5_30
Shirmard HFarahbakhsh EHeidari EBeiranvand Pour APradhan BMüller DChandra R(2022)A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing DataRemote Sensing10.3390/rs1404081914:4(819)Online publication date: 9-Feb-2022
https://doi.org/10.3390/rs14040819
Teja Gontumukkala SSai Varun Godavarthi YRavi Teja Gonugunta BPalaniswamy S(2022)Hand Cricket Game using CNN and MediaPipe2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT54827.2022.9984411(1-6)Online publication date: 3-Oct-2022
https://doi.org/10.1109/ICCCNT54827.2022.9984411

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cover image ACM Other conferences

IPMV '21: Proceedings of the 2021 3rd International Conference on Image Processing and Machine Vision

May 2021

87 pages

ISBN:9781450390040

DOI:10.1145/3469951

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 21 August 2021

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IPMV 2021

IPMV 2021: 2021 3rd International Conference on Image Processing and Machine Vision

May 22 - 24, 2021

Hong Kong, China

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Cited By

Komiya DAkiyoshi M(2023)A Classification Method for “Kawaii” Images Using Four Feature FiltersDistributed Computing and Artificial Intelligence, 20th International Conference10.1007/978-3-031-38333-5_30(296-305)Online publication date: 21-Jul-2023
https://doi.org/10.1007/978-3-031-38333-5_30
Shirmard HFarahbakhsh EHeidari EBeiranvand Pour APradhan BMüller DChandra R(2022)A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing DataRemote Sensing10.3390/rs1404081914:4(819)Online publication date: 9-Feb-2022
https://doi.org/10.3390/rs14040819
Teja Gontumukkala SSai Varun Godavarthi YRavi Teja Gonugunta BPalaniswamy S(2022)Hand Cricket Game using CNN and MediaPipe2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT)10.1109/ICCCNT54827.2022.9984411(1-6)Online publication date: 3-Oct-2022
https://doi.org/10.1109/ICCCNT54827.2022.9984411

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