Sex Classification of Salmon Using Convolutional Neural Network

被引：0
|
作者：
Kuramoto, Takumi [1 ]
Abe, Shuji [2 ]
Ishihata, Hiroaki [1 ]
机构：
[1] Tokyo Univ Technol, Sch Comp Sci, Hachioji, Tokyo, Japan
[2] Tokyo Univ Technol, Sch Biosci & Biotechnol, Hachioji, Tokyo, Japan
来源：
PROCEEDINGS OF THE 2020 14TH INTERNATIONAL CONFERENCE ON UBIQUITOUS INFORMATION MANAGEMENT AND COMMUNICATION (IMCOM) | 2020年
关键词：
Salmon; sex classification; CNN; ternary classification;
D O I：
10.1109/imcom48794.2020.9001787
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this study, we attempted to classify the sex of salmon using a convolutional neural network. We collected labeled(male/female) images of salmon and other fishes, and trained the VGG16 type neural network by implementing several data argumentation techniques, cropping the bounding box of salmon. In evaluation, the F value of the classification result was found to be satisfactory by more than 99%. We demonstrated the focus point of the neural network using Grad-CAM and the classification ability depending on the background processing.
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页数：4
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