ResNet解析：Deep Residual Learning for Image Recognition
Microsoft的ResNet贏得了ILSVRC 2015 和COCO 2015的冠軍。 它是爲了解決在深度神經網絡中，隨着深度的加深，training error會增大。 這顯然不是因爲overfitting，因爲overfitting的表現是在train set上表現很好，test set上表現變差。 它的基本模塊結構如下： 定義公式是： 這裏，x，y分別代表每一層的輸入與輸出。代表殘差，需
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相關文章
- 1. ResNet--Deep Residual Learning for Image Recognition
- 2. [ResNet]Deep Residual Learning for Image Recognition
- 3. ResNet —— Deep Residual Learning for Image Recognition
- 4. ResNet(deep residual learning for image recognition)
- 5. ResNet——Deep Residual Learning for Image Recognition
- 6. 【Deep Learning】ResNet解析：Deep Residual Learning for Image Recognition
- 7. Deep Residual Learning for Image Recognition（ResNet） 閱讀
- 8. Deep Residual Learning for Image Recognition
- 9. Deep Residual Learning for Image Recognition （zh）
- 10. Deep Residual Learning For Image Recognition