A fast image retrieval method with convolutional neural networks

Content-based image retrieval technology is one of the most important research directions in modern image retrieval technology. With the development of deep learning, the effective features of image can be extracted by well-trained convolution neural networks (CNNs). Based on the extracted image features, we can measure the similarity between two images. Directly comparing image similarity on large image dataset can lead to high search accuracy at the cost of low search speed. In this paper, we combined unsupervised learning with approximate nearest neighbor search method to speed up the search process. The results of several experiments prove that our method can simultaneously guarantee the accuracy of the search and the speed of retrieval.