《Very deep convolutional networks for large-scale image recognition》閱後筆記
VGGNet是牛津大學計算機視覺組和DeepMind公司共同研發一種深度卷積網絡，並且在２０１４年在ILSVRC比賽上獲得了分類項目的第二名和定位項目的第一名。 論文主要研究目的： 通過使用具有非常小（3×3）卷積核的架構對深度增加的網絡進行全面評估。探究在大規模圖像識別任務中，卷積網絡深度對模型精確度有何影響。 爲了衡量不同深度對精度造成的影響，所有的ConvNet層配置都採用相
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相關文章
- 1. 論文閱讀筆記--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 2. VGG--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. VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 6. Very Deep Convolutional Networks for Large-Scale Image Recognition
- 7. VGG: VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 8. 論文筆記：Very Deep Convolutional Networks for Large-Scale Image Recognition
- 9. 論文筆記《Very Deep Convolutional Networks for Large-Scale Image Recognition》
- 10. VGGNet 《VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION》學習筆記