athnzc's Stars
zadam/trilium
Build your personal knowledge base with Trilium Notes
dair-ai/ML-Papers-of-the-Week
🔥Highlighting the top ML papers every week.
newren/git-filter-repo
Quickly rewrite git repository history (filter-branch replacement)
prasanthrangan/hyprdots
// Aesthetic, dynamic and minimal dots for Arch hyprland
mviereck/x11docker
Run GUI applications and desktops in docker and podman containers. Focus on security.
Deci-AI/super-gradients
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
dusty-nv/jetson-containers
Machine Learning Containers for NVIDIA Jetson and JetPack-L4T
black0017/MedicalZooPytorch
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
haotian-liu/yolact_edge
The first competitive instance segmentation approach that runs on small edge devices at real-time speeds.
NVlabs/Deep_Object_Pose
Deep Object Pose Estimation (DOPE) – ROS inference (CoRL 2018)
WittmannF/sort-google-scholar
Sorting Google Scholar search results based on the number of citations
IAmSuyogJadhav/3d-mri-brain-tumor-segmentation-using-autoencoder-regularization
Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).
cvlab-epfl/EPnP
EPnP: Efficient Perspective-n-Point Camera Pose Estimation
MyHoneyBadger/awesome-github-wiki
:neckbeard: Awesome list GitHub Wikis
helmut-hoffer-von-ankershoffen/jetson
Helmut Hoffer von Ankershoffen experimenting with arm64 based NVIDIA Jetson (Nano and AGX Xavier) edge devices running Kubernetes (K8s) for machine learning (ML) including Jupyter Notebooks, TensorFlow Training and TensorFlow Serving using CUDA for smart IoT.
ScarletStudy/DGS1-3DS-Release
Release repository for the 3DS version of The Great Ace Attorney - The Adventure of Ryuunosuke Naruhodou
shalabh147/Brain-Tumor-Segmentation-and-Survival-Prediction-using-Deep-Neural-Networks
Use of state of the art Convolutional neural network architectures including 3D UNet, 3D VNet and 2D UNets for Brain Tumor Segmentation and using segmented image features for Survival Prediction of patients through deep neural networks.
martinzlocha/anchor-optimization
Anchor optimization for RetinaNet.
NVIDIA-ISAAC-ROS/isaac_ros_dnn_inference
NVIDIA-accelerated DNN model inference ROS 2 packages using NVIDIA Triton/TensorRT for both Jetson and x86_64 with CUDA-capable GPU
spm/spm
SPM (Statistical Parametric Mapping) - Development Version
swtyree/hope-dataset
HOPE-Image and HOPE-Video 6-DOF pose datasets.
BMIRDS/3dMRISegmentation
Code for NeuroImage: Clinical paper "Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network."
dorianps/LINDA
Lesion Identification with Neighborhood Data Analysis
atinfinity/cudagl
This is a Dockerfile to use OpenGL/CUDA/Vulkan application on Docker container with NVIDIA GPU.
andrewyguo/dope_training
Training, Inference, and Evaluation Scripts for Deep Object Pose
cyd3r/ransac
An implementation of the RANSAC algorithm
rockstreamguy/deepbrain
Deep Learning tools for brain medical images
MayPhu/3D-UNet-Segmenation-for-Brain-Infarction
Nasialink/3dMRISegmentation
Code for NeuroImage: Clinical paper "Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network."
Nasialink/FCN_modified
Modifications of the code for the neural network based on the "3D MRI brain tumor segmentation using autoencoder regularization (FCN)" paper by Andriy Myronenko.