GitHub topics: visual-explanations
haofanwang/Score-CAM
Official implementation of Score-CAM in PyTorch
Language: Python - Size: 2.22 MB - Last synced at: about 1 month ago - Pushed at: almost 3 years ago - Stars: 412 - Forks: 65
LLNL/fastcam
A toolkit for efficent computation of saliency maps for explainable AI attribution. This tool was developed at Lawrence Livermore National Laboratory.
Language: Jupyter Notebook - Size: 20.8 MB - Last synced at: 18 days ago - Pushed at: over 4 years ago - Stars: 45 - Forks: 6
pbiecek/breakDown
Model Agnostics breakDown plots
Language: R - Size: 20.2 MB - Last synced at: 3 days ago - Pushed at: about 1 year ago - Stars: 103 - Forks: 16
ModelOriented/live
Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN
Language: R - Size: 8.46 MB - Last synced at: 15 days ago - Pushed at: over 5 years ago - Stars: 35 - Forks: 5
IDT-ITI/XAI-Deepfakes
Code, model and data for our paper: K. Tsigos, E. Apostolidis, S. Baxevanakis, S. Papadopoulos, V. Mezaris, "Towards Quantitative Evaluation of Explainable AI Methods for Deepfake Detection", Proc. ACM Int. Workshop on Multimedia AI against Disinformation (MAD’24) at the ACM Int. Conf. on Multimedia Retrieval (ICMR’24), Thailand, June 2024.
Language: Python - Size: 61 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 3 - Forks: 2
Purushothaman-natarajan/VALE-Explainer
Language-Aware Visual Explanations (LAVE) is a framework designed for image classification tasks, particularly focusing on the ImageNet dataset. Unlike conventional methods that necessitate extensive training, LAVE leverages SHAP (SHapley Additive exPlanations) values to provide insightful textual and visual explanations.
Language: Jupyter Notebook - Size: 9.32 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 0 - Forks: 0
Purushothaman-natarajan/eXplainable-AI-for-Image-Classification-on-Remote-Sensing
This repository provides the training codes to classify aerial images using a custom-built model (transfer learning with InceptionResNetV2 as the backbone) and explainers to explain the predictions with LIME and GradCAM on an interface that lets you upload or paste images for classification and see visual explanations.
Language: Jupyter Notebook - Size: 48.9 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 2 - Forks: 0
yulongwang12/visual-attribution
Pytorch Implementation of recent visual attribution methods for model interpretability
Language: Jupyter Notebook - Size: 27.7 MB - Last synced at: over 1 year ago - Pushed at: about 5 years ago - Stars: 141 - Forks: 25
vaynexie/CWOX
A XAI Framework to provide Contrastive Whole-output Explanation for Image Classification.
Language: Jupyter Notebook - Size: 117 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 5 - Forks: 0
satyamahesh84/SIDU_XAI_CODE
Similarity Differences and Uniqueness Explainable AI method
Language: Python - Size: 4.56 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 3 - Forks: 1
alexandrosstergiou/Class_Feature_Visualization_Pyramid
[ICCVW 2019] PyTorch code for Class Visualization Pyramid for intpreting spatio-temporal class-specific activations throughout the network
Language: Python - Size: 13 MB - Last synced at: almost 2 years ago - Pushed at: about 5 years ago - Stars: 20 - Forks: 2
