2023年8月28日 · 多维协同注意力（mca）能够有效地结合通道、宽度和高度三个维度的注意力信息，提升网络的表示能力。 轻量化设计：mca引入的参数和计算开销非常小，适合部署在资源受限的设备上。

2012年3月9日 · The official PyTorch implementation of "MCA: Multidimensional collaborative attention in deep convolutional neural networks for image recognition". Approach Figure 1: Schematic comparison of the proposed multidimensional collaborative attention module (d) to the ECA module (a), SRM (b), and CBAM (c).

2023年11月1日 · To alleviate this dilemma, in this paper, we propose a lightweight and efficient multidimensional collaborative attention, MCA, a novel method for simultaneously inferring attention in channel, height, and width dimensions with almost free additional overhead by using a three-branch architecture.

2025年1月3日 · To monitor the condition of cupping spots in real-time during the operation of the automatic cupping machine, reduce the influence of the surrounding environment on the image, and improve the segmentation accuracy of the cupping spots, this paper proposes a network called MCA-Deeplabv3+.

2023年1月30日 · In this work, we introduced a multi-scale Cross Co-Attentional Skip Connection U-Net architecture for the medical image segmentation. Our MCA-UNet utilized the multi-scale feature fusion strategy to combine semantic information at different levels and the cross co-attention module to aggregate relevant global dependencies.

Extensive experimental results for image recognition on CIFAR and ImageNet-1K datasets demonstrate the superiority of our method over other state-of-the-art (SOTA) counterparts. In addition, we also provide insight into the practical benefits of MCA by visually inspecting the GradCAM++ visualization results.

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2010年1月1日 · Morphological component analysis of signals and images has far-reaching applications in science and technology, but some consider it problematic and even intractable. Reproducible research is essential to give MCA a firm scientific foundation.

2021年9月3日 · A computational 3D image generation using a single view with multi-color filter aperture (MCA) and multi-plane representation is a cost-effective approach and most useful when there is no...

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