论文笔记《Very Deep Convolutional Networks for Large-Scale Image Recognition》
VGGNet在2014年的ILSVRC竞赛上，获得了top-1 error的冠军和top-5 error的第二名，错误率分别为24.7%和7.3%，top-5 error的第一名是GoogLeNet 6.7%。在图片定位任务中，也获得了冠军。网络层数由之前的AlexNet 的8层提高到了最高19层（网络E）。其突出贡献在于，证明使用很小的卷积（3*3），增加网络深度，可以有效提升模型的效果。并且V
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相关文章
- 1. 论文笔记：Very Deep Convolutional Networks for Large-Scale Image Recognition
- 2. 论文阅读笔记--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论文翻译
- 10. 盏茶论文CV篇(二) Very Deep Convolutional Networks for Large-Scale Image Recognition