Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks
Aditya Chattopadhay low, Anirban Sarkar, Prantik Howlader low, Vineeth N Balasubramanian
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Citation edge evidence
- Explainable AI: A Review of Machine Learning Interpretability Methods→Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional NetworksLegacy edge — source detail unavailable
- Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks→Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional NetworksLegacy edge — source detail unavailable
- Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks→"Why Should I Trust You?"Legacy edge — source detail unavailable
- Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
- Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks→“Why Should I Trust You?”: Explaining the Predictions of Any ClassifierLegacy edge — source detail unavailable
- Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks→Learning Important Features Through Propagating Activation DifferencesLegacy edge — source detail unavailable
- “Why Should I Trust You?”: Explaining the Predictions of Any Classifier→"Why Should I Trust You?"Legacy edge — source detail unavailable
- Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks→"Why Should I Trust You?"Legacy edge — source detail unavailable
- Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks→Learning Important Features Through Propagating Activation DifferencesLegacy edge — source detail unavailable
- Explainable AI: A Review of Machine Learning Interpretability Methods→"Why Should I Trust You?"Legacy edge — source detail unavailable
- Explainable AI: A Review of Machine Learning Interpretability Methods→Learning Important Features Through Propagating Activation DifferencesLegacy edge — source detail unavailable
What this paper cites, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| "Why Should I Trust You?" | 2016 | 16,210 |
| Distilling the Knowledge in a Neural Network | 2015 | 14,099 |
| “Why Should I Trust You?”: Explaining the Predictions of Any Classifier | 2016 | 5,480 |
| Learning Important Features Through Propagating Activation Differences | 2017 | 2,379 |
What cites it, inside the corpus
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Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record
Topics
| Explainable Artificial Intelligence (XAI) | Computer Science |
| Advanced Neural Network Applications | Computer Science |
| Multimodal Machine Learning Applications | Computer Science |
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