ZeroNAS: Differentiable Generative Adversarial Networks Search for Zero-Shot Learning

In recent years, remarkable progress in zero-shot learning (ZSL) has been achieved by generative adversarial networks (GAN). To compensate for the lack of training samples in ZSL, a surge of GAN architectures have been developed by human experts through trial-and-error testing. Despite their efficac...

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Vydané v:	IEEE transactions on pattern analysis and machine intelligence Ročník 44; číslo 12; s. 9733 - 9740
Hlavní autori:	Yan, Caixia, Chang, Xiaojun, Li, Zhihui, Guan, Weili, Ge, Zongyuan, Zhu, Lei, Zheng, Qinghua
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.12.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Computer architecture Datasets Differentiable architecture search Generative adversarial networks Generators Optimization Search methods Source code Task analysis Testing Training Zero-shot learning
ISSN:	0162-8828, 1939-3539, 2160-9292, 1939-3539
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