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Recently, the convolutional neural network (CNN)-based hashing method has achieved its promising performance for image retrieval. However, tackling the discrepancy between quantization error minimization and discriminability maximization of the network outputs simultaneously still remains unsolved. Distinguished from the previous works, which only can search an equilibrium point within the discrepancy, we propose a novel deep supervised hashing based on stable distribution (DSHSD) to eliminatedoi:10.1109/access.2019.2900489 fatcat:p3mwyez75fc3hlaz7g4bqbz7mm