Research on Underwater Target Recognition Technology Based on Neural Network

نویسندگان

چکیده

At present, the underwater environment required by seafood aquaculture industry is very bad, and fishing operation completed artificially. In this environment, use of machine instead artificial development trend in future. By comparing characteristics different algorithms, multiscale Retinex algorithm (autoMSRCR) selected to deal with image color skew, blur, atomization, other problems. Labelimg software used annotate targets make data sets. Of these, 20% are as test sets, 70% training 10% verification The target detection network You Only Look Once Version4 (YOLOv4) based on convolutional neural networks (CNN) adopted paper. main feature extraction adopts CSPDarknet53 structure, fusion SSP, PANet carries out sampling convolution operations. prediction output extracted features carried through YoloHead network. After recognition model effect obtained testing identification accuracy sea cucumber urchin 90.8% 87.76%, respectively. Experiments show that can accurately identify specified organisms environment.

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ژورنال

عنوان ژورنال: Wireless Communications and Mobile Computing

سال: 2022

ISSN: ['1530-8669', '1530-8677']

DOI: https://doi.org/10.1155/2022/4197178