Abstract:Marine aquaculture is affected by a variety of diseases, and the differences in lesion characteristics are very suitable for image recognition. Based on the above requirements, this study designs a marine breeding disease diagnosis model based on VGG-16 convolutional neural network, and uses a stochastic gradient descent algorithm and overfitting prevention technology to improve the model. The experimental results show that this model is better than other traditional network models, and has high recognition accuracy, generalization ability, and robustness. It can accurately and quickly diagnose diseases with certain expansion and promotion value.