MIST: A simple, scalable, and end-to-end framework for 3D medical imaging segmentation.
-
Updated
Sep 20, 2024 - Python
MIST: A simple, scalable, and end-to-end framework for 3D medical imaging segmentation.
An image segmentation problem completed with Attention U-Net network on breast ultrasound images.
The official repository accompanying the paper "Deep Vision-Based Framework for Coastal Flood Prediction Under Climate Change Impacts and Shoreline Adaptations".
Project of Artificial Intelligence Course | Instructed by DR. MohammadHossein
Deep Learning with CNNs course project
Cerebral Tumor Analysis and Segmentation Web Application
Task: Neural Style Transfer. The implemented solution uses a CycleGan architecture.
A Satellite Semantic Segmentation Project using Unet and Attention Unet with Pytorch,
Project based on Neural Style Transfer, implemented using a CycleGan architecture
Diffusion models from scratch and experiments
Performance of various image segmentation models.
Wound segmentation
a dual Attention U2Net and lightweighting model
Advanced tumor segmentation using Attention U-Net on MIP-PET images for DM i AI 2023.
Deep neural networks in structural health monitoring
"Attention UW-Net: A fully connected model for automatic segmentation and annotation of chest X-ray" by Debojyoti Pal, Pailla Balakrishna Reddy, and Sudipta Roy.
Tackling the challenges of off-road environment navigation through Attention Guided Off-Road Semantic Segmentation.
Projects based on self learning purpose.
Several deep learning methods has applied for example datasets
Add a description, image, and links to the attention-unet topic page so that developers can more easily learn about it.
To associate your repository with the attention-unet topic, visit your repo's landing page and select "manage topics."