State-of-the-Art Deep Learning Models in TensorFlow Modern Machine Learning in the Google Colab Ecosystem

Official implementation of DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation (pytorch implementation)

Classification and segmentation 4 VietNamese foods in using Pytorch

Image segmentation task with KiTS19 challenge data using U-net

Unveiling the secrets of an ancient library buried by Mount Vesuvius, this Kaggle competition, supported by the Vesuvius Challenge organization, tasked participants with detecting ink from 3D X-ray scans of charred scrolls preserved in a Roman villa in Herculaneum.

Semantic segmentation is a type of computer vision technique that assigns a label to every pixel in an image. The label indicates the class of object that the pixel represents. Semantic segmentation is used in tasks such as self-driving cars, where it is important to know not only the boundaries of objects, but also what those objects are.

🏁 ELICE 1st Team Project

road and traffic segmentation with IoU metric and DICE coffecient

An attention-based solution on long-tail 3D point cloud semantic segmentation tasks.

Deep learning based semantic segmentation Using the FCN.

🏁 ELICE 1st Team Project

Repository for semantic segmentation of aerial imagery using U-Net, featuring training scripts, data preprocessing, and model evaluation.

This is a warehouse for DeepLabV3-Xception-pytorch-model, can be used to train your segmentation datasets

[Project&Competition] 2023 장애인 해커톤 대회 - 시각장애인을 위한 보행 방향 및 길 안내 서비스 제안

pre trained deeplabV3 with different backbones

NYU Deep Learning 2023 project for semantic segmentation in video sequences using dual-phase learning with U-Net and ConvLSTM, focusing on predicting segmentation masks from synthetic 3D shape videos.