Identification andclassification of marine ranching fish based on the Faster-RCNN
JIAO Menglu
ZHANG Haiyan
LI Xin
Abstract：Towards the problems of color distortion of the marine ranching observation video and low accuracy of traditional fish identification methods,a marine ranching fish identification and classifica-tion method based on Faster-RCNN was proposed.SDI(Serial Digital Interface)signal color compensa-tion system was used first to improve the poor video quality caused by the particularity and complexity of the marine environments,and then the optimized video was applied to produce data sets with diverse qualities.The Faster-RCNN works following a deep learning model with the feature extraction network and region proposal network(RPN)optimized and used to identify and classify marine ranching fish.The tentative experimental results showed that the mean average precision(mAP)of this method reached 81.63％,significantly improved the accuracy of recognition compared with traditional machine learning target detection algorithms.
Keywords：fish identificationSDI signal color compensationdeep learningfaster-RCNN
Publication Date：2024-06-28
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：8( 65-72 )