Review of Underwater Target Detection in Sonar Images Based on Convolutional Neural Network
As one of the primary means for underwater detection,sonar technology is widely used in marine environments.With the outstanding performance of Convolutional Neural Networks(CNN)in computer vision,this technology has garnered increasing attention from researchers.An overview of the application and development of CNN in sonar image-based underwater target detection is provided,with emphasis on the discussion of typical CNN-based underwater target detection methods.This includes advances and applications of region-based and regression-based detection algorithms tailored to sonar images.Additionally,innovative strategies employed by various network models to address the unique challenges posed by sonar images such as detection with small sample sizes,detection of small targets,and integration of CNN with traditional algorithms,are analyzed.Finally,the current challenges in CNN-based underwater target detection and forecasts the technological trends in this field are summarized.
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