April 1, 2024, 4:45 a.m. | Renkai Wu, Yinghao Liu, Pengchen Liang, Qing Chang

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.20035v1 Announce Type: cross
Abstract: Traditionally for improving the segmentation performance of models, most approaches prefer to use adding more complex modules. And this is not suitable for the medical field, especially for mobile medical devices, where computationally loaded models are not suitable for real clinical environments due to computational resource constraints. Recently, state-space models (SSMs), represented by Mamba, have become a strong competitor to traditional CNNs and Transformers. In this paper, we deeply explore the key elements of parameter …

arxiv cs.cv eess.iv mamba parameters segmentation type unet vision

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