基于深度学习的图像推荐系统

How to extract representative image features and apply them to image retrieval has become one of the focuses in the current research. Through the study of image information, convolutional neural network can effectively extract rich image features, and significantly improve the performance of various image processing tasks. This paper designs and implements the image recommendation system based on deep learning. Firstly, extracte the high-dimensional feature vectors of images by deep learning framework Caffe; Then compress the feature vectors into binary hash codes in the deep learning network by using the local sensitive hash algorithm thought, store the high-dimensional feature vectors and binary codes in the MySQL database, and build the index of binary codes; Finally, the system is tested on the CIFAR-10 dataset, and the results show that it is better than the recommendation systems based on KSH, CNNH, CNNH+, LSH and other hash algorithms.