深度学习论文阅读图像分类篇（六）：SENet《Squeeze-and-Excitation Networks》
Abstract 摘要 Convolutional neural networks are built upon the convolution operation, which extracts informative features by fusing spatial and channel-wise information together within local rece....
深度学习论文阅读图像分类篇（五）：ResNet《Deep Residual Learning for Image Recognition》
Abstract 摘要 Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previousl....
深度学习论文阅读图像分类篇（三）：VGGNet《Very Deep Convolutional Networks for Large-Scale Image Recognition》
Very Deep Convolutional Networks for Large-Scale Image &...
深度学习论文阅读图像分类篇（二）：ZFNet《Visualizing and Understanding Convolutional Networks》
Abstract 摘要 Large Convolutional Network models have recently demonstrated impressive classification performance on the ImageNet benchmark Krizhevsky et al. [18]. However there is no clear under....
深度学习论文阅读图像分类篇（一）：AlexNet《ImageNet Classification with Deep Convolutional Neural Networks》
Abstract 摘要 We trained a large, deep convolutional neural network to classify the1.2 million high-resolution images in the ImageNet LSVRC-2010 contestinto the 1000 different classes. On the tes....
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