VGGNet解析：VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
按照Andrew Ng推薦的順序，精讀了第二篇深度學習的經典論文，下面記錄一些文章中的關鍵點。 以VGG16爲例， 輸入是224x224x3的圖像，下面是每一層的大小： conv1_1 [32, 224, 224, 64] conv1_2 [32, 224, 224, 64] pool1 [32, 112, 112, 64] conv2_1 [32, 112, 112, 128] conv2_2
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相關文章
- 1. 開坑4—VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION（VGGNET詳解）
- 2. Very Deep Convolutional Networks for Large-Scale Image Recognition-VGGNet解讀
- 3. VGGNet論文翻譯—Very Deep Convolutional Networks for Large-Scale Image Recognition
- 4. 圖像識別3-VGGNet-very deep convolutional Network for large-scale image recognition
- 5. VGGNet: Very Deep Convolutional Networks For Large-Scale Image Recognition (2014) 全文翻譯
- 6. VGGNet論文（Very Deep Convolutional Networks for Large-Scale Image Recognition）（譯）
- 7. VGGNet 《VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION》學習筆記
- 8. VGG--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 9. VGG——Very deep convolutional networks for large-scale image recognition
- 10. Very Deep Convolutional NetWorks for Large-Scale Image Recognition