Paper Reading
图像识别
2019/05 [Reading] EfficientNet: Rethinking Model Scaling for Convolutional Neural Network
2019/05 [Reading] Searching for MobileNetV3
2018/07 [Reading] MnasNet: Platform-Aware Neural Architecture Search for Mobile
2018/01 [Reading] MobileNetV2: Inverted Residuals and Linear Bottlenecks
2017/09 [Reading] Squeeze-and-Excitation Networks
2017/07 [Reading] Learning Transferable Architectures for Scalable Image Recognition
2017/07 [Reading] ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices
2017/04 [Reading] MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
2016/11 [Reading] Aggregated Residual Transformations for Deep Neural Networks
2016/10 [Reading] Xception: Deep Learning with Depthwise Separable Convolutions
2016/02 [Reading] Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
2015/12 [Reading] Deep Residual Learning for Image Recognition
2015/12 [Reading] Rethinking the Inception Architecture for Computer Vision
2015/06 [Reading] Spatial Transformer Networks
2014/09 [Reading] Going Deeper with Convolutions
2014/09 [Reading] Very Deep Convolutional Networks For Large-Scale Image Recognition
2013/12 [Reading] Network In Network
2012 [Reading] ImageNet Classification with Deep Convolutional Neural Networks
目标检测和语义分割
2020/4 [Reading] YOLOv4: Optimal Speed and Accuracy of Object Detection
2019/11 [Reading] EfficientDet: Scalable and Efficient Object Detection
2019/04 [Reading] Objects as Points
2018/04 [Reading] YOLOv3: An Incremental Improvement
2017/08 [Reading] Focal Loss for Dense Object Detection
2017/03 [Reading] Mask R-CNN
2016/12 [Reading] YOLO9000: Better, Faster, Stronger
2016/12 [Reading] Feature Pyramid Networks for Object Detection
2015/12 [Reading] SSD: Single Shot MultiBox Detector
2015/06 [Reading] You Only Look Once: Unified, Real-Time Object Detection
2015/06 [Reading] Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
2015/04 [Reading] Fast R-CNN
2013/11 [Reading] Rich feature hierarchies for accurate object detection and semantic segmentation
方法
2016/11 [Reading] Neural Architecture Search with Reinforcement Learning
激活函数
2017/10 [Reading] Searching for Activation Functions
2013 [Reading] Rectifier Nonlinearities Improve Neural Network Acoustic Models