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Single Image Region Algorithm Based on Deep Network

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2021 International Conference on Applications and Techniques in Cyber Intelligence (ATCI 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 81))

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Abstract

This paper designed an image region feature extraction and recognition algorithm based on deep neural network model based on deep network as for the problem that it is hard to extract and recognize the eigenvalue in image region, aiming at accurately extracting image eigenvalue while reducing the consumption of time. Through the experimental test of data set, the rationality and feasibility of the algorithm are confirmed, which can effectively reduce the time consumption and improve the accuracy of image processing.

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Author information

Authors and Affiliations

  1. Research Institute, Lanzhou Jiaotong University, Lanzhou, 730070, Gansu, China

    Junhua Shao & Qiang Li

Authors
  1. Junhua Shao
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  2. Qiang Li
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Corresponding author

Correspondence to Junhua Shao .

Editor information

Editors and Affiliations

  1. Faculty of Science, Engineering and Built Environment, Deakin University, Geelong, VIC, Australia

    Jemal Abawajy

  2. School of Computer Engineering and Sciences, Shanghai University, Shanghai, China

    Zheng Xu

  3. School of Computer Science, University of Oklahoma, Norman, OK, USA

    Mohammed Atiquzzaman

  4. Department of Information Systems and Cyber Security, University of Texas at San Antonio, San Antonio, TX, USA

    Xiaolu Zhang

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© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Shao, J., Li, Q. (2021). Single Image Region Algorithm Based on Deep Network. In: Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 81. Springer, Cham. https://doi.org/10.1007/978-3-030-79197-1_66

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