論文筆記《Very Deep Convolutional Networks for Large-Scale Image Recognition》
VGGNet在2014年的ILSVRC競賽上，獲得了top-1 error的冠軍和top-5 error的第二名，錯誤率分別爲24.7%和7.3%，top-5 error的第一名是GoogLeNet 6.7%。在圖片定位任務中，也獲得了冠軍。網絡層數由之前的AlexNet 的8層提高到了最高19層（網絡E）。其突出貢獻在於，證明使用很小的卷積（3*3），增加網絡深度，可以有效提升模型的效果。並且V
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相關文章
- 1. 論文筆記：Very Deep Convolutional Networks for Large-Scale Image Recognition
- 2. 論文閱讀筆記--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 3. VGG--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 4. VGG——Very deep convolutional networks for large-scale image recognition
- 5. Very Deep Convolutional NetWorks for Large-Scale Image Recognition
- 6. VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 7. Very Deep Convolutional Networks for Large-Scale Image Recognition
- 8. VGG: VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 9. VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION論文翻譯
- 10. 盞茶論文CV篇(二) Very Deep Convolutional Networks for Large-Scale Image Recognition