Zero-Shot Hashing via Asymmetric Ratio Similarity Matrix

Zero-shot hashing targets to learn the hash codes of images in unseen classes based on the limited training data provided by seen classes. In zero-shot hashing, transferring the supervised knowledge, such as attributes and semantic relations, from seen classes to unseen ones is a widely employed met...

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Vydané v:	IEEE transactions on knowledge and data engineering Ročník 35; číslo 5; s. 5426 - 5437
Hlavní autori:	Shi, Yang, Nie, Xiushan, Liu, Xingbo, Yang, Lu, Yin, Yilong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.05.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	asymmetric ratio similarity matrix Asymmetry Binary codes Hamming distance Hash functions Hashing Mathematical analysis Optimization Semantics Similarity Symmetric matrices Visualization zero-shot
ISSN:	1041-4347, 1558-2191
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