论文《Gradient-based learning applied to document recognition》
web:http://yann.lecun.com/exdb/lenet/
论文《ImageNet Classification with Deep Convolutional Neural Networks》
论文《Visualizing and Understanding Convolutional Networks》
arxiv:https://arxiv.org/abs/1311.2901
论文《Very Deep Convolutional Networks for Large-Scale Image Recognition》
web:http://www.robots.ox.ac.uk/~vgg/research/very_deep/
slides:http://www.robots.ox.ac.uk/~karen/pdf/ILSVRC_2014.pdf
论文《Going Deeper with Convolutions》
arxiv:https://arxiv.org/abs/1409.4842
论文《Batch Normalization:Accelerating Deep Network Training by Reducing Internal Covariate Shift》
论文《Rethinking the Inception Architecture for Computer Vision》
arxiv:https://arxiv.org/abs/1512.00567
一个5×5的卷积核可以由2次3×3的卷积代替
一个3×3的卷积核可以由1×3和3×1的卷积代替
原始Inception结构
把5×5的卷积由2次3×3的卷积代替后的Inception结构
把n×n的卷积由1×n和n×1的卷积代替后的Inception结构
论文《Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning》
arxiv:https://arxiv.org/abs/1602.07261
Inception-v4
论文《Deep Residual Learning for Image Recognition》
arxiv:https://arxiv.org/abs/1512.03385
论文《SqueezeNet:AlexNet-level accuracy with 50x fewer parameters and 0.5MB model size》
论文《Densely Connected Convolutional Networks》
arxiv:https://arxiv.org/abs/1608.06993
论文《Xception: Deep Learning with Depthwise Separable Convolutions》
arxiv:https://arxiv.org/abs/1610.02357
论文《Aggregated Residual Transformations for Deep Neural Networks》
arxiv:https://arxiv.org/abs/1611.05431
论文《PolyNet: A Pursuit of Structural Diversity in Very Deep Networks》
arxiv:https://arxiv.org/abs/1611.05431
论文《MobileNets:Efficient Convolutional Neural Networks for Mobile Vision Applications》
论文《ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices》
论文《Dual Path Networks》
arxiv:https://arxiv.org/abs/1707.01629
论文《Learning transferable architectures for scalable image recognition》
论文《Squeeze-and-Excitation Networks》
论文《Inverted Residuals and Linear Bottlenecks:Mobile Networks for Classification, Detection and Segmentation》