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MTFCN: Multi-task Fully Convolutional Network for Cow Face Detection

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Communications, Signal Processing, and Systems (CSPS 2020)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 654))

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Abstract

Automatic cow detection with computer vision is a hitting topic in recent years. Recent studies found that adding facial alignment task can improve the performance of the detection. Instead of using the cascaded method to fine tune the candidate boxes, we propose an end-to-end multi-task fully convolutional network (MTFCN) which outperforms multi-task cascaded convolutional networks (MTCNN) on the collected cow dataset. In addition, focal loss is adopted to focus on hard samples that are hard to be classified by the original model. The addressed network has an average precision (AP) with 91.71%, while the AP of MTCNN is 88.11% on our own cow dataset.

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Acknowledgements

This work is supported by the Key Special Project National Key R&D Program of China (2018YFC1604000) and “the Fundamental Research Funds for the Central Universities,” Huazhong Agricultural University (Grant Number: 2662017PY119).

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Authors and Affiliations

  1. College of Informatics, Huazhong Agricultural University, Wuhan, Hubei, 430070, China

    Ziyan Wang, Fuchuan Ni & Na Yao

  2. Hubei Engineering Technology Research Center of Agricultural Big Data, Wuhan, Hubei, 430070, China

    Ziyan Wang, Fuchuan Ni & Na Yao

  3. College of Information Engineering, Tarim University, Alaer, Xinjiang, 843300, China

    Na Yao

Authors
  1. Ziyan Wang
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  2. Fuchuan Ni
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  3. Na Yao
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Corresponding author

Correspondence to Fuchuan Ni .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. Tianjin Normal University, Tianjin, China

    Wei Wang

  3. Dalian University of Technology, Dalian, China

    Xin Liu

  4. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  5. Huazhong Agricultural University, Wuhan, China

    Xiaoxia Li

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Wang, Z., Ni, F., Yao, N. (2021). MTFCN: Multi-task Fully Convolutional Network for Cow Face Detection. In: Liang, Q., Wang, W., Liu, X., Na, Z., Li, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2020. Lecture Notes in Electrical Engineering, vol 654. Springer, Singapore. https://doi.org/10.1007/978-981-15-8411-4_147

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  • DOI: https://doi.org/10.1007/978-981-15-8411-4_147

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-8410-7

  • Online ISBN: 978-981-15-8411-4

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