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Online Adaptive Supervised Hashing for Large-Scale Cross-Modal Retrieval
2020
IEEE Access
In recent years, with the continuous growth of multimedia data on the Internet, multimodal hashing has attracted increasing attention for its efficiency in large-scale cross-modal retrieval. Typically, most existing multimodal hashing methods are batch-based methods that cannot deal with the growing streaming data. Online multimodal hashing adopts online learning strategy to learn hash models incrementally, which can process large-scale streaming data. However, existing supervised online
doi:10.1109/access.2020.3037968
fatcat:hj2e3wiy35cufpwzpbzv2miure