Research Notes
Personal notes on research papers, primarily focused on deep learning and computer vision.
CNN Architectures
- AlexNet. Krizhevsky, Alex et al. “ImageNet Classification with Deep Convolutional Neural Networks.” NIPS (2012).
Computer Vision with Deep Learning
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R-CNN. 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.
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FCN. 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
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Why Fine Tuning. 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.
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U-Net. Ronneberger, Olaf et al. “U-Net: Convolutional Networks for Biomedical Image Segmentation.” MICCAI (2015).
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Camelyon16 Winner. Wang, Dayong et al. “Deep Learning for Identifying Metastatic Breast Cancer.” CoRR abs/1606.05718 (2016): n. pag.
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kU-Net & BDC-LSTM. Chen, Jianxu et al. “Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation.” NIPS (2016).