Shah et al. "SAM4EM: Efficient Memory-Based Two Stage Prompt-Free Segment Anything Model Adapter for Complex 3D Neuroscience Electron Microscopy Stacks." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025.
Markdown
[Shah et al. "SAM4EM: Efficient Memory-Based Two Stage Prompt-Free Segment Anything Model Adapter for Complex 3D Neuroscience Electron Microscopy Stacks." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025.](https://mlanthology.org/cvprw/2025/shah2025cvprw-sam4em/)
BibTeX
@inproceedings{shah2025cvprw-sam4em,
title = {{SAM4EM: Efficient Memory-Based Two Stage Prompt-Free Segment Anything Model Adapter for Complex 3D Neuroscience Electron Microscopy Stacks}},
author = {Shah, Uzair and Agus, Marco and Boges, Daniya and Chiappini, Vanessa and Alzubaidi, Mahmood and Schneider, Jens and Hadwiger, Markus and Magistretti, Pierre J. and Househ, Mowafa S. and Calì, Corrado},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2025},
pages = {4678-4687},
url = {https://mlanthology.org/cvprw/2025/shah2025cvprw-sam4em/}
}