Generalized Zero-Shot Learning Using Conditional Wasserstein Autoencoder

Generalized zero-shot learning (GZSL) is a technique to train a deep learning model to identify unseen classes. Conventionally, conditional generative models have been employed to generate training data for unseen classes from the attribute. In this paper, we propose a new conditional generative mod...

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Vydané v:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) s. 3413 - 3417
Hlavní autori:	Kim, Junhan, Shim, Byonghyo
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 23.05.2022
Predmet:	Acoustics Benchmark testing Conferences Data models Deep learning Generalized zero-shot learning generative adversarial network generative model Signal processing Training data variational autoencoder
ISSN:	2379-190X
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