Pinned Repositories
anonymize-slide
Delete the label from a whole-slide image
awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
Brain-Tumor-Segmentation-and-Analysis
This will help researchers to find the important papers, databases etc. associated with BTS and analysis
BraTS-Toolkit
Code to preprocess, segment, and fuse glioma MRI scans based on the BraTS Toolkit manuscript.
deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
Deep-Learning-Notes
FeTSChallenge2022
The repo for the FeTS Challenge
fl-tutorial
This is for FL tutorial at MICCAI 2022
GaNDLF
A generalizable application framework for segmentation, regression, and classification using PyTorch
Python-Tutorial-with-Examples
This tutorial will help to learn basics of Python Programming
ujjwalbaid0408's Repositories
ujjwalbaid0408/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
ujjwalbaid0408/Python-Tutorial-with-Examples
This tutorial will help to learn basics of Python Programming
ujjwalbaid0408/anonymize-slide
Delete the label from a whole-slide image
ujjwalbaid0408/awesome-semantic-segmentation
:metal: awesome-semantic-segmentation
ujjwalbaid0408/Brain-Tumor-Segmentation-and-Analysis
This will help researchers to find the important papers, databases etc. associated with BTS and analysis
ujjwalbaid0408/BraTS-Toolkit
Code to preprocess, segment, and fuse glioma MRI scans based on the BraTS Toolkit manuscript.
ujjwalbaid0408/Deep-Learning-Notes
ujjwalbaid0408/FeTSChallenge2022
The repo for the FeTS Challenge
ujjwalbaid0408/fl-tutorial
This is for FL tutorial at MICCAI 2022
ujjwalbaid0408/GaNDLF
A generalizable application framework for segmentation, regression, and classification using PyTorch
ujjwalbaid0408/LabelFusion
Implementation of various label fusion approaches for medical imaging.
ujjwalbaid0408/medical-datasets
tracking medical datasets, with a focus on medical imaging
ujjwalbaid0408/github-action-workshop
ujjwalbaid0408/github-actions-workshop
ujjwalbaid0408/github-actions-workshop_new
ujjwalbaid0408/ITCR2023_1
ujjwalbaid0408/LatexAuthorListBraTS
ujjwalbaid0408/medperf
An open benchmarking platform for medical artificial intelligence using Federated Evaluation.
ujjwalbaid0408/ObjectRecognition
Uses the iOS device camera and a custom deep learning algorithm to perform object recognition.
ujjwalbaid0408/OTTR_Template_Website
ujjwalbaid0408/Pytorch-UNet
Pytorch implementation of the U-Net for image semantic segmentation, with dense CRF post-processing
ujjwalbaid0408/qubiq
ujjwalbaid0408/Radiomics
ujjwalbaid0408/Refuge2020
ujjwalbaid0408/TensorFlow-Tutorials
TensorFlow Tutorials with YouTube Videos
ujjwalbaid0408/Tutorials
Here, we will be showcasing our seminar series “CPP for Image Processing and Machine Learning” including presentations and code examples. There are image processing and machine learning libraries out there which use C++ as a base and have become industry standards (ITK for medical imaging, OpenCV for computer vision and machine learning, Eigen for linear algebra, Shogun for machine learning). The documentation provided with these packages, though extensive, assume a certain level of experience with C++. Our tutorials are intended for those people who have basic understanding of medical image processing and machine learning but who are just starting to get their toes wet with C++ (and possibly have prior experience with Python or MATLAB). Here we will be focusing on how someone with a good theoretical background in image processing and machine learning can quickly prototype algorithms using CPP and extend them to create meaningful software packages.
ujjwalbaid0408/tutorials-1
MONAI Tutorials
ujjwalbaid0408/ujjwalbaid.github.io
Github Pages template for academic personal websites