Generative adversarial network based on chaotic time series
Abstract Generative adversarial networks (GANs) are becoming increasingly important in the artificial construction of natural images and related functionalities, wherein two types of networks called generators and discriminators evolve through adversarial mechanisms. Using deep convolutional neural...
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Autores principales: | Makoto Naruse, Takashi Matsubara, Nicolas Chauvet, Kazutaka Kanno, Tianyu Yang, Atsushi Uchida |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
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Materias: | |
Acceso en línea: | https://doaj.org/article/c3385cc93b1e4d298997877832cffd10 |
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