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SSD-Mobilenet Implementation for Classifying Fish Species

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Intelligent Computing and Optimization (ICO 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1072))

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Abstract

Vietnam has large but outdated fishing industry. A high-accuracy classification model could bring about positive impacts on fisheries management systems, fish finding support system, or market support systems. The challenge is that there are many objects appearing in an image of a fish net and that fish of the same species can have very different features. The objective of this paper is to provide a method to classify fish species automatically via images. The method presented is a combination of the advantages of both the SSD and Mobilenet models in order to provide the needed high accuracy. This model is can also be implemented in applications that run on a variety ofplatforms.

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Author information

Authors and Affiliations

  1. FPT University, Hanoi, Vietnam

    Phan Duy Hung & Nguyen Ngoc Kien

Authors
  1. Phan Duy Hung
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  2. Nguyen Ngoc Kien
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Corresponding author

Correspondence to Phan Duy Hung .

Editor information

Editors and Affiliations

  1. Department of Fundamental and Applied Sciences, Universiti Teknologi Petronas, Tronoh, Perak, Malaysia

    Pandian Vasant

  2. Computer Science, FEI, VSB-TU Ostrava, Ostrava, Czech Republic

    Ivan Zelinka

  3. Faculty of Engineering Management, Poznan University of Technology, Poznan, Poland

    Gerhard-Wilhelm Weber

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Hung, P.D., Kien, N.N. (2020). SSD-Mobilenet Implementation for Classifying Fish Species. In: Vasant, P., Zelinka, I., Weber, GW. (eds) Intelligent Computing and Optimization. ICO 2019. Advances in Intelligent Systems and Computing, vol 1072. Springer, Cham. https://doi.org/10.1007/978-3-030-33585-4_40

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