2017 Mask R-CNN《Mask R-CNN》_1650003834704.pdf
Deep learning for steganalysis via convolutional neural networks_1650003835201.pdf
Deep learning is a good steganalysis tool when embedding key_1650003835414.pdf
2016 Faster R-CNN《Faster R-CNN Towards Real-Time Object》_1650003833481.pdf
2015 Fast R-CNN《Fast R-CNN》_1650003832971.pdf
2014 R-CNN《Rich feature hierarchies for accurate object detection and semantic segmentation》_1650003832244.pdf
Li_Selective_Kernel_Networks_CVPR_2019_paper_1650003831011.pdf
Residual_Attention_1650003831407.pdf
Chen_SCA-CNN_Spatial_and_CVPR_2017_paper_1650003830129.pdf
Hu_Squeeze-and-Excitation_Networks_CVPR_2018_paper_1650003830395.pdf
2019《TensorMask A Foundation for Dense Object Segmentation》v1_1650003828722.pdf
CBAM_1650003829734.pdf
2019 全景FPN《Panoptic Feature Pyramid Networks》v1_1650003827947.pdf
2019 NAS《Auto-DeepLab Hierarchical Neural Architecture Search for Semantic Image Segmentation》v1_1650003827054.pdf
2018 全景分割《Panoptic Segmentation》v2_1650003825813.pdf
2018 神经网络搜索实现语义分割《Searching for Efficient Multi-Scale Architectures for Dense Image Prediction》_1650003826377.pdf
2017 Large Kernel Matters《Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network》_1650003825006.pdf
2017 MobileNets《MobileNets Efficient Convolutional Neural Networks for Mobile Vision Applications》_1650003825485.pdf
2017 DeepLab v3+《Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation》v3_1650003823791.pdf
2017 DeepLab v3《Rethinking Atrous Convolution for Semantic Image Segmentation》v3_1650003824344.pdf
2016 RefineNet《RefineNet Multi-Path Refinement Networks for High-Resolution Semantic Segmentation》v3_1650003822749.pdf
2016 PSPNet《Pyramid Scene Parsing Network》v2_1650003821871.pdf
2016 DeepLab v2《DeepLab Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution,and Fully Connected CRFs》v2_1650003821059.pdf
2015 SegNet《SegNet A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation》v3_1650003819812.pdf
2015 U-Net《U-Net Convolutional Networks for Biomedical》_1650003820396.pdf
2015 DeconvNet《Learning Deconvolution Network for Semantic Segmentation》_1650003818687.pdf
2015 Dilated Convolutions《MULTI-SCALE CONTEXT A GGREGATION BY》v3_1650003819282.pdf
2014 FCN《Fully Convolutional Networks for Semantic Segmentation》v2_1650003817896.pdf
2014 DeepLab v1《SEMANTIC IMAGE SEGMENTATION WITH DEEP CONVOLUTIONAL NETS AND FULLY CONNECTEDCRFs》 _1650003817247.pdf
2017 Mask R-CNN《Mask R-CNN》v3_1650003816098.pdf
《Mask Scoring R-CNN》_1650003816870.pdf
2016 Xception《Xception Deep Learning with Depthwise Separable Convolutions》v3_1650003814916.pdf
2015 BN《Batch Normalization Accelerating Deep Network Training by Reducing Internal Covariate Shift》v3_1650003815085.pdf
《A guide to convolution arithmetic for deep》_1650003815197.pdf
《Bag of Tricks for Image Classification with Convolutional Neural Networks》v2_1650003815382.pdf
2018 PAN《Pyramid Attention Network for Semantic Segmentation》_1650003815534.pdf
2016 DenseNet《Densely Connected Convolutional Networks 》v5_1650003813839.pdf
2016 Inception v4《Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning》v2_1650003814284.pdf
2016 ResNet《Identity Mappings in Deep Residual Networks》v3_1650003814517.pdf
2014 VGGNet《Very Deep Convolutional Networks for Large-Scale image recognition》_1650003812898.pdf
2015 Inception v2《Batch Normalization Accelerating Deep Network Training by Reducing Internal Covariate Shift》v3_1650003813176.pdf
2015 Inception v3《Rethinking the Inception Architecture for Com》v3_1650003813367.pdf
2015 ResNet《Deep Residual Learning for Image Recognition》_1650003813528.pdf
2014 GoogLeNet-Inception v1《Going deeper with convolutions》_1650003811878.pdf
2014 SPPNet《Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognitionv4》_1650003812421.pdf
2012 AlexNet《ImageNet Classification with Deep Convolutional》_1650003811303.pdf
DeepLearningBookCN_1650003799608.pdf
DeepLearningBook_1650003796902.pdf
CS231n课程笔记翻译：神经网络笔记2_1650003794984.pdf
CS231n课程笔记翻译：神经网络笔记3_1650003795290.pdf
CS231n课程笔记翻译：线性分类笔记_1650003795573.pdf
CS231n课程笔记翻译：卷积神经网络笔记_1650003793892.pdf
CS231n课程笔记翻译：反向传播笔记_1650003794204.pdf
CS231n课程笔记翻译：图像分类笔记_1650003794456.pdf
CS231n课程笔记翻译：最优化笔记_1650003794643.pdf
CS231n课程笔记翻译：神经网络笔记1_1650003794804.pdf
CS231n课程笔记翻译：Python Numpy教程_1650003793495.pdf