Modality-Invariant Asymmetric Networks for Cross-Modal Hashing

Cross-modal hashing has garnered considerable attention and gained great success in many cross-media similarity search applications due to its prominent computational efficiency and low storage overhead. However, it still remains challenging how to effectively take multilevel advantages of semantics...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering 2023-05, Vol.35 (5), p.5091-5104
Hauptverfasser:	Zhang, Zheng, Luo, Haoyang, Zhu, Lei, Lu, Guangming, Shen, Heng Tao
Format:	Artikel
Sprache:	eng
Schlagworte:	Alignment Asymmetry binary code learning Binary codes cross-modal hashing Deep asymmetric learning Electronic mail Feature extraction Heterogeneity Invariants Learning Measurement modality-alignment network Redundancy Representation learning Semantics Similarity Training
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