JSAI2018
Jun 5 - Jun 8, 2018Kagoshima-shi, Kagoshima-ken (Shiroyama Kanko Hotel)
JSAI2018
Jun 5 - Jun 8, 2018Kagoshima-shi, Kagoshima-ken (Shiroyama Kanko Hotel)
[1B2-OS-11b-02]Verification of Fish Species Estimation Model Based on Echo Sounder Image
〇Yudai Hirama1, Soichiro Yokoyama1, Tomohisa Yamashita1, Hidenori Kawamura1, Keiji Suzuki2, Masaaki Wada2(1. Hokkaido University, 2. Future University Hakodate)
Keywords:
Sonar Image,Convolutional Neural Network,Set-Net
The overfishing and depletion of marine resources including tuna have become problems in Japan. Managing to marine resource is necessary to increase catch amount. However, set-net is difficult to separate fish speceis. Therefore, this research used a sonar image obtained by an echo sounder installed in a set-net. We verify of fish species estimation model based on echo sounder image.