Use Deep Learning model to diagnose 14 pathologies on Chest X-Ray and use GradCAM Model Interpretation Method

Based on the mmdetection framework, compute various salience maps for object detection.

This repo is special for those who want to start learning computer vision related tasks such as image classification.

Implementation or LRP and Object detection on Brain scans to detect Brain Tumor and Alzhimers

code for studying OpenAI's CLIP explainability

Making CNNs interpretable.

One of the first implementations of Grad-CAM ++ for time series / 1d signal.

这是一个用于计算ViT及其变种模型的GradCAM自动脚本，可以自动处理批量的图像 A GradCAM automatic script to visualize the model result

Custom Keras Callbacks for Feature Visualization, Class Activation Map, Grad-CAM

Used the Functional API to built custom layers and non-sequential model types in TensorFlow, performed object detection, image segmentation, and interpretation of convolutions. Used generative deep learning including Auto Encoding, VAEs, and GANs to create new content.

Three different DNN models Xception, In- ceptionV3, and VGG19 were used for the classification of crop disease from the image dataset, and explainable AI XAI was used to evaluate their performance. InceptionV3 was achieved as the best model with the highest accuracy of 97.20% accuracy.

Demonstration of potential in digital pathology applications from a CNN-based model to classify tumor vs normal histopathology image patches, applying transfer learning and Grad-CAM for interpretability.

This repository explores the fascinating world of brain tumor classification using cutting-edge Convolutional Neural Networks (CNNs) and eXplainable Artificial Intelligence (XAI) techniques.

Saliency Enhancing with Scaling and Sliding

Applying GradCAM method with 3 kinds of CNN-based model for NLP classification task on french dataset.

Example of how to use MATLAB to produce post-hoc explanations (using Grad-CAM and image LIME) for a medical image classification task.

A simple implementation of GradCAM (Gradient-weighted Class Activation Mapping) using PyTorch and OpenCV.

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

This repository consists of models of CNN for classifying different types of charts. Moreover, it also includes script of fine-tuned VGG16 for this task. On top of that CradCAM implementation of fine-tuned VGG16.

Keras implementation for GradCAM analysis for dual 3D CNN model.