ASRWGAN: Wasserstein Generative Adversarial Network for Audio Super Resolution
ASEGAN：WGAN音频超分辨率 这篇文章并不具有权威性，因为没有发表，说不定是外国的某个大学的毕业设计，或者课程结束后的作业、或者实验报告。 CS230: Deep Learning, Spring 2018, Stanford University, CA. (LateX template borrowed from NIPS 2017.) 作者：Jonathan Gomes-Selman,
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相关文章
- 1. ASRWGAN: Wasserstein Generative Adversarial Network for Audio Super Resolution
- 2. 论文翻译：ASRWGAN: Wasserstein Generative Adversarial Network for Audio Super Resolution
- 3. 论文翻译：Speech Super Resolution Generative Adversarial Network
- 4. Time-Frequency Networks For Audio Super-Resolution
- 5. ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks, ECCV2018
- 6. 论文解读《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》SRGAN
- 7. 论文阅读——Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
- 8. 《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》阅读笔记
- 9. Generative Adversarial Network-based Image Super-Resolution using Perceptual Content Losses
- 10. 论文阅读之《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》