image thumbnail

Grad-CAM for AlexNet to explain the reason of classification

version 1.0.1 (8.17 MB) by Takuji Fukumoto
Grad-CAM for visual explanation with re-trained AlexNet

243 Downloads

Updated 25 Dec 2020

From GitHub

View license on GitHub

Class Activation Mapping(CAM) is a good method to explain why the model classify the object as that.
https://jp.mathworks.com/matlabcentral/fileexchange/69357-class-activation-mapping
But network models which can be applied for CAM are limited.
Grad-CAM is the method to generalize CAM to work with many kinds of networks.

Through this demo, you can learn workflow from retraining model(AlexNet) to applying Grad-CAM on it.

[Japanese]
CNNを用いたディープラーニングによる分類の判定精度は非常に高く、多くの領域での画像自動判定に利用されています。一方で、内部がブラックボックスで「なぜその判定になったのかわからない」点に不安を感じる方もいます。Class Activation Mapping(CAM)は判定要因の可視化に非常に便利ですが、適用できるネットワークに制限があります。

Grad-CAMはGradietを利用して任意のネットワーク・層でCAMを一般化した方法です。
このサンプルでAlexNetでの転移学習からGrad-CAMの適用までのコードを確認できます。

[Keyword]
画像処理・IPCVデモ・ディープラーニング・深層学習・転移学習・入門・物体認識・画像分類・コンピュータビジョン・ニューラルネットワーク・人工知能・外観検査・可視化

Paper:
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization.
Ramprasaath R. Selvaraju, etc
https://arxiv.org/abs/1610.02391

Cite As

Takuji Fukumoto (2021). Grad-CAM for AlexNet to explain the reason of classification (https://github.com/mathworks/Grad-CAM-for-AlexNet-to-explain-the-reason-of-classification/releases/tag/1.0.1), GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.