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# 3,230
Python
Keras
deeplea...
semanti...
61 commits

CNN-heatmap

1. Visualizing and Understanding Convolutional Networks
https://arxiv.org/pdf/1311.2901v3.pdf
https://neukom.dartmouth.edu/docs/bbat-wacv2016.pdf
http://cs231n.github.io/understanding-cnn/

  1. Net surgery trick http://cs231n.github.io/convolutional-networks/#convert https://github.com/BVLC/caffe/blob/master/examples/net_surgery.ipynb

https://leonardoaraujosantos.gitbooks.io/artificial-inteligence/content/image_segmentation.html https://arxiv.org/pdf/1502.02766v3.pdf https://arxiv.org/pdf/1411.4038v2.pdf http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Long_Fully_Convolutional_Networks_2015_CVPR_paper.pdf https://arxiv.org/pdf/1605.06211v1.pdf

convert fully connected layers to their equivalent convolutional layers, since the weights are the same and only the shapes are different.

  1. Global average pooling layer Network In Network https://arxiv.org/pdf/1312.4400.pdf

  2. Learning Deep Features for Discriminative Localization http://cnnlocalization.csail.mit.edu/ https://github.com/jacobgil/keras-cam

  3. Grad-CAM: Gradient-weighted Class Activation Mapping https://github.com/ramprs/grad-cam http://gradcam.cloudcv.org/ https://arxiv.org/pdf/1610.02391v2.pdf

  4. Is object localization for free? – Weakly Supervised Object Recognition with Convolutional Neural Networks http://www.di.ens.fr/willow/research/weakcnn/ http://www.di.ens.fr/willow/research/cnn/

Additional: ~~~

  1. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps https://arxiv.org/pdf/1312.6034v2.pdf

  2. Top-down NeuralAttention by Excitation Backprop (c-MWP) https://arxiv.org/pdf/1608.00507v1.pdf http://cs-people.bu.edu/jmzhang/excitationbp.html

  3. Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer https://arxiv.org/pdf/1612.03928v1.pdf https://github.com/szagoruyko/attention-transfer

  4. Visualizing Deep Neural Network Decisions: Prediction Difference Analysis https://openreview.net/pdf?id=BJ5UeU9xx https://github.com/lmzintgraf/DeepVis-PredDiff A New Method to Visualize Deep Neural Networks https://icmlviz.github.io/assets/papers/23.pdf

  5. Self-Taught Object Localization with Deep Network https://arxiv.org/pdf/1409.3964.pdf

  6. Shallow and Deep Convolutional Networks for Saliency Prediction https://github.com/imatge-upc/saliency-2016-cvpr ~~~

Keras codebase: ~~~ https://github.com/raghakot/keras-vis

Oclusion based technique: https://github.com/waleedka/cnn-visualization/blob/master/cnn_visualization.ipynb

Net surgery trick: https://github.com/heuritech/convnets-keras

GAP-CAM https://github.com/alexisbcook/ResNetCAM-keras/ https://github.com/jacobgil/keras-cam https://github.com/tdeboissiere/VGG16CAM-keras https://github.com/keras-team/keras/blob/0cfa5c2709906a7a76f552f71a562f899e408695/examples/classactivationmaps.py

Grad-CAM https://github.com/jacobgil/keras-grad-cam https://github.com/hiveml/tensorflow-grad-cam

https://raghakot.github.io/keras-vis/visualizations/attention/

https://github.com/mlhy/ResNet-50-for-Cats.Vs.Dogs ~~~

Tensorflow codebase: ~~~ GAP https://github.com/sjchoi86/tensorflow-101/blob/master/notebooks/gap_mnist.ipynb

GAP-CAM https://github.com/jazzsaxmafia/Weakly_detector

Grad-CAM https://github.com/Ankush96/grad-cam.tensorflow

PyTorch codebase:

Grad-CAM https://github.com/kazuto1011/grad-cam-pytorch https://github.com/jacobgil/pytorch-grad-cam

GAP-CAM https://github.com/metalbubble/CAM/blob/master/pytorch_CAM.py

SPN https://github.com/yeezhu/SPN.pytorch

https://github.com/utkuozbulak/pytorch-cnn-visualizations

https://github.com/jacobgil/pytorch-explain-black-box ~~~

Regression Activation Map https://github.com/cauchyturing/kagglediabeticRAM

Other ~~~ https://github.com/metalbubble/cnnvisualizer

https://github.com/InFoCusp/tf_cnnvis

https://github.com/ppwwyyxx/tensorpack/tree/master/examples/Saliency

https://github.com/InFoCusp/tf_cnnvis

https://github.com/keplr-io/quiver

https://jacobgil.github.io/deeplearning/vehicle-steering-angle-visualizations https://jacobgil.github.io/deeplearning/class-activation-maps

https://jacobgil.github.io/deeplearning/filter-visualizations https://jacobgil.github.io/computervision/saliency-from-backproj

https://github.com/CSAILVision/NetDissect

https://medium.com/merantix/picasso-a-free-open-source-visualizer-for-cnns-d8ed3a35cfc5

https://github.com/CSAILVision/NetDissect http://netdissect.csail.mit.edu/

https://github.com/imatge-upc/saliency-salgan-2017

http://imatge-upc.github.io/saliency-2016-cvpr/ https://github.com/imatge-upc/saliency-2016-cvpr

https://openreview.net/pdf?id=SkfMWhAqYQ

https://thegradient.pub/a-visual-history-of-interpretation-for-image-recognition/ https://thegradient.pub/interpretability-in-ml-a-broad-overview/

Visualization:

https://github.com/shaohua0116/Activation-Visualization-Histogram ~~~

To look at: ~~~ http://blog.qure.ai/notes/visualizingdeeplearning https://github.com/utkuozbulak/pytorch-cnn-visualizations https://github.com/fornaxai/receptivefield ~~~

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