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The project includes SRAM In Memory Computing Accelerator, by researchers mentioned below under the supervision of Prof: Manan Suri (NVM & Neuromorphic Hardware Research Group IIT-Delhi, https://we…
Reinforcement learning project using deep Q-learning to control the operations of an electrical microgrid
Deep Reinforcement Learning Techniques for Energy Management of Networked Microgrids
collection of works aiming at reducing model sizes or the ASIC/FPGA accelerator for machine learning
Open Source Library for GPU-Accelerated Execution of Trained Deep Convolutional Neural Networks on Android
Online Crash Gambling Game Web App Built with the MERN Stack
The food ordering & delivery application designed based on the real-life scenario. Anyone can use this code on their own purpose. If you are interested please make your contribution to the code.
Federated learning tutorial given as part of the University of Queensland course on Advanced Embedded Systems 2023
Federated Learning project for the course "Advanced Machine Learning" at Politecnico di Torino
Implementation of “DreamDiffusion: Generating High-Quality Images from Brain EEG Signals”
Data and code for Shen, Horikawa, Majima, and Kamitani (2019) Deep image reconstruction from human brain activity. PLoS Comput. Biol. http:https://dx.doi.org/10.1371/journal.pcbi.1006633.
This repo provides the official code for : 1) TransBTS: Multimodal Brain Tumor Segmentation Using Transformer (https://arxiv.org/abs/2103.04430) , accepted by MICCAI2021. 2) TransBTSV2: Towards Bet…
Pytorch implementation of pooling-regularized GNN (PRGNN) for fMRI analysis. https://arxiv.org/pdf/2007.14589.pdf
# AD-Prediction Convolutional Neural Networks for Alzheimer's Disease Prediction Using Brain MRI Image ## Abstract Alzheimers disease (AD) is characterized by severe memory loss and cognitive impai…
Resurces for MRI images processing and deep learning in 3D
Segmentation deep learning ALgorithm based on MONai toolbox: single and multi-label segmentation software developed by QIMP team-Vienna.
[MICCAI2022] This is an official PyTorch implementation for A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation
PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty
Official Pytorch Implementation of "Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Network" (accepted by MICCAI 2019)
A pytorch implementation for variational network for MRI reconstruction
A high-level, easy-to-deploy non-uniform Fast Fourier Transform in PyTorch.
pytorch dataset class for reading and transforming NIfTI files
A large-scale dataset of both raw MRI measurements and clinical MRI images.
Building an ACL tear detector to spot knee injuries from MRIs with PyTorch (MRNet)
MRI analysis using PyTorch and MedicalTorch