Multi-Scale-Attention
Image segmentation framework
A deep learning framework for medical image segmentation using multi-scale guided attention mechanisms to improve accuracy and reduce irrelevant information.
Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"
461 stars
16 watching
96 forks
Language: Python
last commit: over 4 years ago
Linked from 1 awesome list
attention-mechanismbiomedical-image-analysisdeep-learningencoder-decoderpytorch
mrgloom/awesome-semantic-segmentationRelated projects:
| Repository | Description | Stars |
|---|---|---|
 fyu/dilation | This project provides a deep learning framework implementing dilated convolutions for semantic image segmentation | 782 |
 aitorzip/keras-icnet | A deep learning framework for real-time image segmentation on high-resolution images using convolutional neural networks | 86 |
 facebookresearch/cutler | An unsupervised object detection and segmentation framework that can learn from image data alone, without requiring human annotations. | 954 |
 tobypde/frrn | A software framework for training and evaluating full-resolution residual networks for semantic image segmentation tasks | 280 |
 sacmehta/espnet | A deep learning framework for semantic segmentation on edge devices. | 542 |
 zhengpeng7/birefnet | An open-source implementation of an image segmentation model that combines background removal and object detection capabilities. | 1,484 |
 mitmul/chainer-pspnet | An implementation of a deep learning-based image segmentation algorithm in Chainer | 74 |
 guosheng/refinenet | A MATLAB-based framework for semantic image segmentation and dense prediction tasks using multi-path refinement networks. | 589 |
 zhujun98/semantic_segmentation | Implementations of deep learning architectures for semantic segmentation of images in various datasets. | 6 |
 aharley/segaware | An open-source software framework for building segmentation-aware convolutional networks with local attention masks | 146 |
 timosaemann/enet | A deep neural network architecture for real-time semantic segmentation in images | 585 |
 akolesnikoff/sec | Proposes an approach to weakly-supervised image segmentation using a composite loss function | 245 |
 preritj/segmentation | Deep learning models for semantic segmentation of images | 101 |
| mitmul/ssai-cnn | Semantic segmentation using convolutional neural networks for aerial and satellite images | 260 |
 cvjena/cn24 | A framework for building semantic segmentation models using convolutional patch networks | 123 |