🍅🍅🍅YOLOv5-Lite: Evolved from yolov5 and the size of model is only 900+kb (int8) and 1.7M (fp16). Reach 15 FPS on the Raspberry Pi 4B~

The best React-based framework with performance, scalability and security built in.

Run a Jupyter Notebook to detect, track, and count cars in a video using Maximo Visual Insights (formerly PowerAI Vision) and OpenCV

Multiple file upload plugin with image previews, drag and drop, progress bars. S3 and Azure support, image scaling, form support, chunking, resume, pause, and tons of other features.

An optimizer that trains as fast as Adam and as good as SGD.

Django CAS 1.0/2.0/3.0 client authentication library, supporting Django 4.2+ and Python 3.8+

Vehicle Speed Check

Keras implementation of https://arxiv.org/abs/1510.07391

Code for analyzing medical images saved as .dicom files

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Squeeze using mxnet

An all-in-one Deep Learning toolkit for image classification to fine-tuning pretrained models using MXNet.

Transfer Learning Suite in Keras. Perform transfer learning using any built-in Keras image classification model easily!

Caffe: a fast open framework for deep learning.

BraTs (Brain Tumor Segmentation)

Deep learning based skull stripping and FLAIR abnormality segmentation in brain MRI using U-Net

U-Net Brain Tumor Segmentation

Awesome GAN for Medical Imaging

chainer catgan

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

👩‍💻👨‍💻 Awesome cheatsheets for popular programming languages, frameworks and development tools. They include everything you should know in one single file.

An online platform based on adversarial training for pixel wise classification on medical images.

MRI medical image segmentation

Brain tumor classification on structural MR images of BraTS dataset based on 3D Multi-Scale Convolutional Neural Network, which is a part of my master thesis project.

Alzheimer's Disease Detection from structural brain MR images of ADNI dataset by 3D Multi-Scale Convolutional Neural Network, which is a part of my master thesis project.

Preprocessing pipeline on Brain MR Images through FSL and ANTs, including registration, skull-stripping, bias field correction, enhancement and segmentation.

The project aims at comparing results achieved by Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA) in segmentation of MRIs of Brain Tumor. The above mentioned algorithms are…