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Deep Discriminative Supervised Hashing via Siamese Network
2017
IEICE transactions on information and systems
The latest deep hashing methods perform hash codes learning and image feature learning simultaneously by using pairwise or triplet labels. However, generating all possible pairwise or triplet labels from the training dataset can quickly become intractable, where the majority of those samples may produce small costs, resulting in slow convergence. In this letter, we propose a novel deep discriminative supervised hashing method, called DDSH, which directly learns hash codes based on a new
doi:10.1587/transinf.2017edl8126
fatcat:7k4ljo4fbjdj3eafyhjybtdyna