Fast recognition of cat and dog images based on network compression

Cat and dog recognition is a classic problem in the field of image recognition. This paper proposes a fast detection algorithm FAST-CD-Classification-Net for this problem. The algorithm improves F1 from 0.7299 to 0.9875 with the help of residual structure; The product acceleration network reduces the running time from 0.025s to 0.008s without significantly reducing the accuracy. Experiments on the data set CD-KAGGLE show that the accuracy and robustness of the recognition algorithm designed in this paper are better than other algorithms.