https://github.com/mrcfps/paper-notes

Notes on research papers.
https://github.com/mrcfps/paper-notes

artificial-intelligence deep-learning pattern-recognition research research-paper

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Notes on research papers.

• Host: GitHub
• URL: https://github.com/mrcfps/paper-notes
• Owner: mrcfps
• Created: 2018-10-28T12:38:55.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2018-12-09T11:32:16.000Z (about 6 years ago)
• Last Synced: 2024-11-05T15:50:35.537Z (about 2 months ago)
• Topics: artificial-intelligence, deep-learning, pattern-recognition, research, research-paper
• Language: TeX
• Homepage:
• Size: 2.22 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Research Notes

Personal notes on research papers, primarily focused on deep learning and computer vision.

## CNN Architectures

- [AlexNet](./cnn-architectures/alexnet/alexnet.pdf). *Krizhevsky, Alex et al. “ImageNet Classification with Deep Convolutional Neural Networks.” NIPS (2012).*

## Computer Vision with Deep Learning

- [R-CNN](./computer-vision-with-deep-learning/r-cnn/r-cnn.pdf). *Girshick, Ross B. et al. “Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation.” 2014 IEEE Conference on Computer Vision and Pattern Recognition (2014): 580-587.*

- [FCN](./computer-vision-with-deep-learning/fcn/fcn.pdf). *Shelhamer, Evan et al. “Fully Convolutional Networks for Semantic Segmentation.” 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015): 3431-3440.*

## Medical Image Processing

- [Why Fine Tuning](./medical-images/why-fine-tuning/why-fine-tuning.pdf). *Tajbakhsh, Nima et al. “Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?” IEEE Transactions on Medical Imaging 35 (2016): 1299-1312.*

- [U-Net](./medical-images/u-net/u-net.pdf). *Ronneberger, Olaf et al. “U-Net: Convolutional Networks for Biomedical Image Segmentation.” MICCAI (2015).*

- [Camelyon16 Winner](./medical-images/camelyon16-winner/camelyon16-winner.pdf). *Wang, Dayong et al. “Deep Learning for Identifying Metastatic Breast Cancer.” CoRR abs/1606.05718 (2016): n. pag.*

- [kU-Net & BDC-LSTM](./medical-images/kunet-bdclstm/kunet-bdclstm.pdf). *Chen, Jianxu et al. “Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation.” NIPS (2016).*