VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
VGG和AlexNet都是很经典的模型。而VGG也是在AlexNet的基础之上进行改进的。AlexNet每层仅仅含有一个Convolution层，filter的大小7x7；VGG每层含有2~4个Conv层，filter的大小是3x3（能感受空间最小的filter）。 个人认为，整个文章相比于AlexNet最大的亮点就是更深的卷积层，以及最小的filter。 在本文中，作者讨论了ConvNet架构设
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相关文章
- 1. VGG--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
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- 5. Very Deep Convolutional Networks for Large-Scale Image Recognition
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- 10. [VGG论文详解](2014)Very Deep Convolutional Networks For Large-Scale Image Recognition