Understanding the ecological environment, population abundance, and growth status of marine organisms in the marine fishery is important to promote its sustainability. However, existing manual detection methods can cause some damage to marine ecology and are difficult to meet the demand for fast and accurate detection. In addition, light, shadows, and disturbances in the marine ecosystem can affect the effectiveness of intelligent detection methods. To address these problems, a deep residual convolutional neural network (DRCNN) based on hybrid attention mechanism (HAM) is proposed to detect ma...
