Standardization of Sonar Images by Conditional Random Fields for Fish Segmentation with Mask R-CNN

Chin Chun Chang, Yen Po Wang, Shyi Chyi Cheng

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Imaging sonar systems are widely used for monitoring fish behavior in turbid or low ambient light waters. In this paper, Mask R-CNN is adopted for segmenting fish in sonar images. A preprocessing convolutional neural network (PreCNN) is proposed to provide "standardized"feature maps for Mask R-CNN and to ease applying Mask R-CNN trained for one fish farm to the others. Experimental results have shown that Mask R-CNN on the output of PreCNN is more accurate than Mask R-CNN directly on sonar images. Applying Mask R-CNN plus PreCNN trained for one fish farm to new fish farms is also more effective.

原文English
主出版物標題ISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems
主出版物子標題5G Dream to Reality, Proceeding
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781665419512
DOIs
出版狀態Published - 2021
事件2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021 - Hualien, 台灣
持續時間: 16 11月 202119 11月 2021

出版系列

名字ISPACS 2021 - International Symposium on Intelligent Signal Processing and Communication Systems: 5G Dream to Reality, Proceeding

Conference

Conference2021 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2021
國家/地區台灣
城市Hualien
期間16/11/2119/11/21

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