very deep convolutional networks for lorge-scale image recognition(VGG)閱讀總結
文章目錄 1 網絡結構及對比 2 創新點 2.1 小的卷積核 2.2 多尺度進行訓練和測試 3 網絡的訓練和評估 3.1 參數 3.2 訓練和測試 3.3 評估 4 結論 1 網絡結構及對比 A → E：網絡層從11到19層 A → A-LPN：添加了反應歸一化層沒有改善 B：增加了卷積層數 C: 添加了1×1的卷積層，相當於加入了非線性層（Relu） D：將1×1換成3×3說明肥牛蓋飯的感受野表
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相關文章
- 1. Very Deep Convolutional NetWorks for Large-Scale Image Recognition
- 2. Very Deep Convolutional Networks for Large-Scale Image Recognition
- 3. VGG——Very deep convolutional networks for large-scale image recognition
- 4. VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 5. 論文閱讀——VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 6. 論文閱讀：VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION（VGG）
- 7. 論文閱讀筆記--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 8. 《Very Deep Convolutional Networks for Large-Scale Image Recognition》論文閱讀
- 9. VGG: VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 10. VGG--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION