Faizanuddin Ansari's repositories
torchxrayvision
TorchXRayVision: A library of chest X-ray datasets and models.
awesome-gan-for-medical-imaging
Awesome GAN for Medical Imaging
balanced_mixup
Repository for MICCAI 2021 paper Balanced-MixUp for Highly Imbalanced Medical Image Classification
build-basic-generative-adversarial-networks-gans
Notebook 1 : Goal In this notebook, you're going to create your first generative adversarial network (GAN) for this course! Specifically, you will build and train a GAN that can generate hand-written images of digits (0-9). You will be using PyTorch in this specialization, so if you're not familiar with this framework, you may find the PyTorch documentation useful. The hints will also often include links to relevant documentation. Learning Objectives Build the generator and discriminator components of a GAN from scratch. Create generator and discriminator loss functions. Train your GAN and visualize the generated images.
coding-interview-university
A complete computer science study plan to become a software engineer.
DeTraC_COVId19
Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network
dgl
Python package built to ease deep learning on graph, on top of existing DL frameworks.
google-research
Google Research
home
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
ImageNet21K
Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(NeurIPS, 2021) paper
learn2learn
A PyTorch Library for Meta-learning Research
lime
Lime: Explaining the predictions of any machine learning classifier
machine-learning-imbalanced-data
Code repository for the online course Machine Learning with Imbalanced Data
machine_learning_complete
A comprehensive repository containing 30+ notebooks on learning machine learning!
mixup-cifar10
mixup: Beyond Empirical Risk Minimization
Neural-Image-Captioning-with-Object-Detection-and-Attention-Mechanism
Image captioning is a task which lies in the intersection of areas of object detection and natural language processing. We will be proposing a, model which will be utilizing both the areas of CV and NLP for the automatic generation of the captions of the given image. Model that we are going to propose mimics the human visual system that automatically describe image content. Main idea of our model is that rather than focusing on the whole image it is better to focus on particular areas like the areas where objects are present in the image. Our model consists of two sub model, first sub model or an encoder consist of object detection part which is used to identify the object in the given image along with their spatial location and finally making annotation vector consist of object features and their spatial feature. Second sub model or decoder consist of RNN based LSTM network along attention network which produce a context vector based on annotation vector at a particular time and finally at each step LSTM takes input of attention network along with the other input to generate caption of a given image. Experimental result on the MSCOCO dataset shows that our model outperforms previous benchmark models.
PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
pytorch-grad-cam
Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM
SSL4MIS
Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.
stat453-deep-learning-ss21
STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2021)
TailCalibX
Pytorch implementation of Feature Generation for Long-Tail Classification by Rahul Vigneswaran, Marc T Law, Vineeth N Balasubramaniam and Makarand Tapaswi
torch-cam
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM)
vit-pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
xrays-and-gradcam
Classification and Gradient-based Localization of Chest Radiographs using PyTorch.