Why do deep convolutional networks generalize so poorly to small image transformations?論文筆記
文章目錄 1. Introduction 2. Failures of modern CNNs 3. Ignoring the Sampling Theorem 4. Why don't modern CNNs learn to be invariant from data? 5. Quantifying partial invariance Conclusion Attention: 論文解讀的
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相關文章
- 1. Why do deep convolutional networks generalize so poorly to small image transformations?
- 2. [深度學習論文筆記][arxiv 1805] Why do deep convolutional networks generalize so poorly to small image transf
- 3. 論文筆記：Very Deep Convolutional Networks for Large-Scale Image Recognition
- 4. 論文閱讀筆記（五十六）：Image Super-Resolution Using Deep Convolutional Networks
- 5. 論文閱讀筆記--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 6. 論文筆記《Very Deep Convolutional Networks for Large-Scale Image Recognition》
- 7. 【論文筆記-VDSR】Accurate Image Super-Resolution Using Very Deep Convolutional Networks
- 8. 論文閱讀筆記（四十二）：Visualizing and Understanding Convolutional Networks
- 9. [CVPR2017] Weakly Supervised Cascaded Convolutional Networks論文筆記
- 10. 論文閱讀筆記（五十三）：Understanding Deep Convolutional Networks