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In this paper, most of the existing Hashing methods is mapping the hand extracted features to binary code, and designing the loss function with the label of images. However, hand-crafted features and inadequacy considering all the loss of the network will reduce the retrieval accuracy. Supervised hashing method improves the similarity between sample and hash code by training data and labels of image. In this paper, we propose a novel deep hashing method which combines the objective functiondoi:10.1051/matecconf/201817303032 fatcat:2vj3snalnvffxekkgatjs7i27q