Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

🍔🍟🍗 Food analysis baseline with Theseus. Integrate object detection, image classification and multi-class semantic segmentation 🍞🍖🍕

keras implementation of unet plus plus

Decoder architecture based on the UNet++. Combining residual bottlenecks with depthwise convolutions and attention mechanisms, it outperforms the UNet++ in a coronary artery segmentation task, while being significantly more computationally efficient.

🏥 医学图像作业：图像配准论文阅读；眼底血管分割实验

Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.

Logiciel de détection, localisation & segmentation de carries sur des radiographies dentaires.

Clean Implementation of Unet3+ and validation on Cityscapes dataset.

3D car detection competition on Kaggle : https://www.kaggle.com/c/pku-autonomous-driving/overview

Model for Doctor's Cyclop Project at FPT Edu Hackathon 2021

[🥉 3rd place] AI-powered web application able to track changes in the urban landscape

UNet and UNet++ implemented in Tensorflow

Brain MRI segmentation using segmentation models

Training code for Vesuvius Kaggle Competition

Task to create a model that can automatically segment the stomach and intestines on MRI scans.

Code Implementation of the article "A Framework for Real-Time Volcano-Seismic Event Recognition Based on Multi-Station Seismograms and Semantic Segmentation Models" (under review).