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Research Summary of Convolution Neural Network in Image Recognition

Authors:

Ji LiuAuthors Info & Claims

ICDPA 2018: Proceedings of the International Conference on Data Processing and Applications

Pages 39 - 44

https://doi.org/10.1145/3224207.3224219

Published: 12 May 2018 Publication History

Abstract

Convolution neural networks is a model of deep learning and it is popular in image recognition, object detection and speech recognition. This paper studied Convolution neural networks in detail. Firstly this paper introduced the generation and development of convolution neural networks and illustrated its advantages in image recognition tasks. Then, it summarized the classic structure of convolution neural networks. Next, this paper stated the study trends and summarized five aspects: appropriately simplified networks, reducing over-fitting, increasing gradient signal, deeper networks and randomization. Finally, this paper discussed the problems existed in convolution neural networks and looked forward to the development trends

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Cited By

Zhu AChen SLu FMa CZhang F(2021)Recognition Method of Tunnel Lining Defects Based on Deep LearningWireless Communications and Mobile Computing10.1155/2021/90701822021(1-12)Online publication date: 30-Sep-2021
https://doi.org/10.1155/2021/9070182
Samaddar MRoy RDe SKarmakar R(2021)A Comparative Study of Different Machine Learning Algorithms on Bitcoin Value Prediction2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)10.1109/ICAECT49130.2021.9392629(1-7)Online publication date: 19-Feb-2021
https://doi.org/10.1109/ICAECT49130.2021.9392629

Index Terms

Research Summary of Convolution Neural Network in Image Recognition
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Neural networks

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cover image ACM Other conferences

ICDPA 2018: Proceedings of the International Conference on Data Processing and Applications

May 2018

73 pages

ISBN:9781450364188

DOI:10.1145/3224207

Copyright © 2018 ACM.

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Peking University: Peking University
Guangdong University of Technology: Guangdong University of Technology

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 May 2018

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ICDPA 2018

ICDPA 2018: ICDPA 2018, International Conference on Data Processing and Applications

May 12 - 14, 2018

Guangdong, China

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Cited By

Zhu AChen SLu FMa CZhang F(2021)Recognition Method of Tunnel Lining Defects Based on Deep LearningWireless Communications and Mobile Computing10.1155/2021/90701822021(1-12)Online publication date: 30-Sep-2021
https://doi.org/10.1155/2021/9070182
Samaddar MRoy RDe SKarmakar R(2021)A Comparative Study of Different Machine Learning Algorithms on Bitcoin Value Prediction2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)10.1109/ICAECT49130.2021.9392629(1-7)Online publication date: 19-Feb-2021
https://doi.org/10.1109/ICAECT49130.2021.9392629

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