Papers and books to read to start deep learning
This list of papers provide a good introduction to deep learning in computer vision field. My notes on these papers are here.
Most popular network architectures
- AlexNet https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks
- VGG16 https://arxiv.org/abs/1409.1556
- GoogLeNet (Inception) https://arxiv.org/abs/1409.4842
- ResNet (Residual Network) https://arxiv.org/abs/1512.03385
- DenseNet https://arxiv.org/abs/1608.06993
- Dual Path Network https://arxiv.org/abs/1707.01629
Object detection
- Overview article https://blog.athelas.com/a-brief-history-of-cnns-in-image-segmentation-from-r-cnn-to-mask-r-cnn-34ea83205de4
- R-CNN https://arxiv.org/abs/1311.2524
- Fast RCNN https://arxiv.org/abs/1504.08083
- Faster RCNN https://arxiv.org/abs/1506.01497
- YOLO https://arxiv.org/abs/1506.02640
- YOLO 9000 https://arxiv.org/abs/1612.08242
- SSD https://arxiv.org/abs/1512.02325
Segmentatoin
- FCN https://arxiv.org/abs/1605.06211
- UNet https://lmb.informatik.uni-freiburg.de/people/ronneber/u-net/
- 3D UNet: https://arxiv.org/abs/1606.06650
- (3D) VNet: https://arxiv.org/abs/1606.04797
- Mask RCNN https://arxiv.org/abs/1703.06870
- Polygon RNN https://arxiv.org/pdf/1704.05548.pdf
- MultiPath Network https://arxiv.org/abs/1604.02135
- DeepMask https://arxiv.org/abs/1506.06204
- SharpMask https://arxiv.org/abs/1603.08695
Books on deep learning
- Deep Learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville, http://www.deeplearningbook.org/
- Deep Learning with Python, Francois Chollet
- Deep Reinforcement Learning Hands-On, Maxim Lapan
- Reinforcement Learning: An Introduction, Richard S. Sutton and Andrew G. Barto
- The Elements of Statistical Learning, 2nd Edition (ESLII, very mathematical on ML)
- https://web.stanford.edu/~hastie/Papers/ESLII.pdf
- Introduction of Statistical Learning (ISL, dumbed down version of ESLII)
- http://www-bcf.usc.edu/~gareth/ISL/