Paper Reading


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

2016/11 [Reading] Neural Architecture Search with Reinforcement Learning

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

2015/02 [Reading] Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

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


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


2015/02 [Reading] Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift


2017/10 [Reading] Searching for Activation Functions

2013 [Reading] Rectifier Nonlinearities Improve Neural Network Acoustic Models