ASRWGAN: Wasserstein Generative Adversarial Network for Audio Super Resolution
ASEGAN：WGAN音頻超分辨率 這篇文章並不具有權威性，因爲沒有發表，說不定是外國的某個大學的畢業設計，或者課程結束後的作業、或者實驗報告。 CS230: Deep Learning, Spring 2018, Stanford University, CA. (LateX template borrowed from NIPS 2017.) 作者：Jonathan Gomes-Selman,
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相關文章
- 1. ASRWGAN: Wasserstein Generative Adversarial Network for Audio Super Resolution
- 2. 論文翻譯：ASRWGAN: Wasserstein Generative Adversarial Network for Audio Super Resolution
- 3. 論文翻譯：Speech Super Resolution Generative Adversarial Network
- 4. Time-Frequency Networks For Audio Super-Resolution
- 5. ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks, ECCV2018
- 6. 論文解讀《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》SRGAN
- 7. 論文閱讀——Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
- 8. 《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》閱讀筆記
- 9. Generative Adversarial Network-based Image Super-Resolution using Perceptual Content Losses
- 10. 論文閱讀之《Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network》