Awesome_Mamba

Awesome_Mamba

Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis

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Awesome Mamba is a curated collection of groundbreaking research papers and articles on Mamba Architecture, a pioneering framework in deep learning known for its selective state spaces and efficiency in processing complex data structures. The repository offers a comprehensive exploration of Mamba architecture through categorized research papers covering various domains like visual recognition, speech processing, remote sensing, video processing, activity recognition, image enhancement, medical imaging, reinforcement learning, natural language processing, 3D recognition, multi-modal understanding, time series analysis, graph neural networks, point cloud analysis, and tabular data handling.

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Awesome Mamba

Awesome License: MIT

🔥🔥 This is a collection of awesome articles about Mamba models (With a particular emphasis on Medical Image Analysis)🔥🔥

Citation

@misc{heidari2024computationefficient,
      title={Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis}, 
      author={Moein Heidari and Sina Ghorbani Kolahi and Sanaz Karimijafarbigloo and Bobby Azad and Afshin Bozorgpour and Soheila Hatami and Reza Azad and Ali Diba and Ulas Bagci and Dorit Merhof and Ilker Hacihaliloglu},
      year={2024},
      eprint={2406.03430},
      archivePrefix={arXiv},
      primaryClass={eess.IV}
}

Updates

  • 😎 First release: June 05, 2024

Table of Contents

Surveys

Preliminaries and State Space Models

Architecture Redesign

Remote Sensing

Speech Processing

Video Processing

Activity Recognition

Image Enhancement

Image-Video-Generation

Medical Imaging

Image Segmentation

Reinforcement Learning

Natural Language Processing

3D Recognition

Multi-Modal Understanding

Time Series

GNN

Point Cloud

Tabular Data

Star History

Star History Chart

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