gradcam-visualization
There are 2 repositories under gradcam-visualization topic.
RuoyuChen10 / objectdetection-saliency-maps
Based on the mmdetection framework, compute various salience maps for object detection.
Language:Jupyter Notebook 80LaurentVeyssier / Chest-X-Ray-Medical-Diagnosis-with-Deep-Learning
Use Deep Learning model to diagnose 14 pathologies on Chest X-Ray and use GradCAM Model Interpretation Method
Language:Jupyter Notebook 71faizahkureshi232 / DoctorLRP
Implementation or LRP and Object detection on Brain scans to detect Brain Tumor and Alzhimers
Language:Jupyter Notebook 38Harry-KIT / Image-Classification-on-small-datasets-in-Pytorch
This repo is special for those who want to start learning computer vision related tasks such as image classification.
Language:Python 37sMamooler / CLIP_Explainability
code for studying OpenAI's CLIP explainability
Language:Jupyter Notebook 33- cnn_explainer
gsurma / cnn_explainer
Making CNNs interpretable.
Language:Jupyter Notebook 19 Mahiro2211 / GradCAM_Auto
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
Language:Jupyter Notebook 17marcusnk237 / Gradcam_plus_plus
One of the first implementations of Grad-CAM ++ for time series / 1d signal.
Language:Jupyter Notebook 16ayulockin / interpretabilitycnn
Custom Keras Callbacks for Feature Visualization, Class Activation Map, Grad-CAM
Language:Jupyter Notebook 15Ankit-Kumar-Saini / Coursera_TensorFlow_Advanced_Techniques_Specialization
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.
coursera-specializationobject-detectiontensorflow2variational-autoencodersmodel-interpretabilitygradcam-visualizationsaliency-mapimage-segmentationfunctional-apiauto-encodersmask-rcnngenerative-adversarial-networksgradient-tape-optimizationcustom-training-loopscustom-loss-functionscustom-layerscustom-model-developmentretina-netLanguage:Jupyter Notebook 10- Language:Jupyter Notebook 8
SalehAhmedShafin / XAI-and-Deep-Neural-Networks-for-Crop-Disease-Detection-and-Interpretability
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.
Language:Jupyter Notebook 8AniketP04 / TumorNet-GradCAM
This repository explores the fascinating world of brain tumor classification using cutting-edge Convolutional Neural Networks (CNNs) and eXplainable Artificial Intelligence (XAI) techniques.
Language:Jupyter Notebook 7ENSAE-CKW / nlp_understanding
Applying GradCAM method with 3 kinds of CNN-based model for NLP classification task on french dataset.
Language:Python 6ashishpatel26 / GRADCAM-Tensorflow2-Visual-Explainable-AI
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Language:Python 5ogemarques / xai-matlab
Example of how to use MATLAB to produce post-hoc explanations (using Grad-CAM and image LIME) for a medical image classification task.
Language:MATLAB 5devsonni / Chart-Classification-Using-CNN----Keras
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.
Language:Python 4xmuyzz / Dual3dCNN-GradCAM-Keras
Keras implementation for GradCAM analysis for dual 3D CNN model.
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SalvatoreRa / CNNscan
A CT-scan of your CNN
Language:Python 3the-mercury / CIHMLC
Chest X-ray Classification
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akashAD98 / grad_cam-pytorch-custom
cnn model interpretablity
Language:Python 2AkashVS01 / Covid-detection-using-XAI
CNN architectures Resnet-50 and InceptionV3 have been used to detect whether the CT scan images is covid affected or not and prediction is validated using explainable AI frameworks LIME and GradCAM.
Language:Jupyter Notebook 2Dipeshtamboli / Interactive-GradCAM
Easy to follow GradCAM visualization - Google collab notebooks where you just have to upload the image and mention the target class to get the feature visualization for models trained on COCO and Imagenet dataset.
Language:Jupyter Notebook 2faizan1234567 / Recognition-and-gradient-based-localization-of-chest-radiographs
Disease diagnoses in chest radiographs with different neural network architectures, and models activations localization using grad-cam. The whole implementation is in Pytorch.
Language:Jupyter Notebook 2nikhilroxtomar / GradCAM-in-PyTorch
A simple implementation of GradCAM (Gradient-weighted Class Activation Mapping) using TensorFlow and OpenCV.
Language:Python 2Example of how to use MATLAB to produce post-hoc explanations (using Grad-CAM) for image classification tasks.
santoshd97 / Automated_Diagnosis_with_Visualization_from_X-Rays
X-Ray diagnosis and heatmap visualization of disease area using deep learning models like VGG-16 and Grad-CAM with 86% accuracy
Language:Jupyter Notebook 2shahariar-shibli / Explainable-Cost-Sensitive-Deep-Neural-Networks-for-Brain-Tumor-Detection-from-Brain-MRI-Images
Paper under review on "Multimedia Tools and Applications" journal.
Language:Jupyter Notebook 2- CHB-image_classification_GradCam
tekboart / CHB-image_classification_GradCam
Using four different CNN architectures in an endeavor to detect built heritage in need of preservation and approximately localize the existent damage therein using the GradCam technique.
Language:Jupyter Notebook 2 abdel-habib / ISIC2019-skin-lesion-classification-segmentation
ISIC2019 skin lesion classification (binary & multi-class) as well as segmentation pipelines using VGG16_BN and visual attention blocks. The project features improving the results found in the literature by implementing an ensemble architecture. This project was developed for "Computer Aided Diagnosis - CAD" course for MAIA masters program.
Language:Jupyter Notebook 1Apurv090405 / Visualize-activation-maps-for-age-detection.
This project aims to predict the age of individuals from images using a pre-trained ResNet50 model. We preprocess the dataset, train the model, and visualize the results using Grad-CAM.
Language:Jupyter Notebook 1shub-garg / Hybrid-Lung-Segmentation-Disease-Classification-and-Severity-Localization
A project for lung disease detection and analysis using deep learning. It includes lung segmentation, disease classification, and severity localization with Grad-CAM for visual explanations. This repository provides code, datasets, and documentation for replication and further research.
Language:Jupyter Notebook 1TmohamedashrafT / Mushroom-Classification-with-Grad-cam
This repository aims to implement a mushroom type classifier using PyTorch, utilizing various models to enhance performance. Additionally, the project includes an analysis of the model's performance using Gradient-Class Activation Map (Grad-CAM) visualization.
Language:Jupyter Notebook 1yjwong1999 / GradCAM-for-YOLOv3
Most tutorials on GradCAM are made for Image Classification tasks. This repo will provide an example of GradCAM for object detection using YOLOv3.
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