In this project I'm going to segment Tumor in MRI brain Images with a UNET which is based on Keras. The dataset is available online on Kaggle, and the algorithm provided 99% accuracy with a validation loss of 0.11 in just 10 epochs.

Demo to segment brain MRI FLAIR

Implementing U-Net Semantic Segmentation from Scratch for Carvana Image Masking Challenge

Tensorflow implementation of U-Net model with TPU Estimator support.

in this study, i have designed unet neural network model from scratch. i also have used new method that i invented for traning data model.so i was able to increase accurance rate to 0,96

Model to segment 3D MRI images using a 3D UNET based FCN architecture and convert it to a surface mesh. Please see the link below for the full paper.

Brain Tumour Segmentation with TrUE-Net tool - top 10 DL model in MICCAI BraTS 2020

This repository shows information about the solution of our team joining the competition, namely UIT Car Racing 2022. Although the project has some hesitations about algorithms for controller, all of the machine learning methods have been optimized for hardware that can easily to build up FPS to serve for real-time operating system.

Pytorch implementation of some of the popular papers

Landcover classification on sentinel-2 data with Prithvi, EfficientNet-Unet and OSM / CNES Landcover labels.

U-Net Like Pretrained Model For Human Body Segmentation

Efficient model for semantic segmentation on edge devices, specifically targeting the analysis of disaster scenes from images captured by unmanned aerial vehicles (UAVs).

A General Medical Image Segmentation Framework.(Multi-Modal, Mono-Modal, 2D, 3D)

Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.

Pytorch implementation of the U-Net for image semantic segmentation, with dense CRF post-processing

百度车道线比赛

Convolutional Neural Networks: (1) based on UNet; (2) FCN8 for Image Segmentation of Pascal VOC 2012 dataset written as part of my MSc in Artificial Intelligence degree. Written in Tensorflow 2.0 with Keras Functional API.

Image Segmentation with UNET

5 input channels UNET semantic segmentation for aerial image classifier