June 11, 2024, 4:50 a.m. | Abbas Khan, Muhammad Asad, Martin Benning, Caroline Roney, Gregory Slabaugh

cs.CV updates on arXiv.org arxiv.org

arXiv:2406.05786v1 Announce Type: new
Abstract: Convolutional Neural Networks (CNNs) and Transformer-based self-attention models have become standard for medical image segmentation. This paper demonstrates that convolution and self-attention, while widely used, are not the only effective methods for segmentation. Breaking with convention, we present a Convolution and self-Attention Free Mamba-based semantic Segmentation Network named CAF-MambaSegNet. Specifically, we design a Mamba-based Channel Aggregator and Spatial Aggregator, which are applied independently in each encoder-decoder stage. The Channel Aggregator extracts information across different channels, …

abstract arxiv attention become breaking cnns convention convolution convolutional convolutional neural networks cs.cv free image mamba medical network networks neural networks paper segmentation self-attention semantic standard transformer type while

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