medical-imaging adversarial-learning deformable-image-registration abdominal-ct-registration brain-mri-registration self-and-cross-attentions Updated Jul 29, 2024 Python Improve this page Add a description, image, and links to the self-and-cross-attentions topic page so that developers can more ea...
Motivation: 显存的attention模型中,对于attention没有直接的监督信号,所以本文提出了两个模块,在attention的过程中加入了监督信号,如下图所示: 1)CCR使得模型能够关注到相关的区域(尽可能多地关注到相关区域--更多,high recall) 2)CCS使得模型能够区分出主体区域和背景区域(尽可能的关注到更相关的区域---更准,high ...
Cross-domain orchestrationAttention conciliation moduleRecursive multi-scale convolutionThe ready accessibility of high-resolution image sensors has stimulated interest in increasing depth resolution by leveraging paired color information as guidance. Nevertheless, how to effectively exploit the depth and color ...
In this paper, we propose a novel SSL method based on Cross Distillation of Multiple Attentions (CDMA) to effectively leverage unlabeled images. Firstly, we propose a Multi-attention Tri-branch Network (MTNet) that consists of an encoder and a three-branch decoder, with each branch using a ...
offical code for: Semi-supervised Pathological Image Segmentation via Cross Distillation of Multiple Attentions. MICCAI 2023. - HiLab-git/CDMA
A.pay attention toB.pay attentions to C.pay attention onD.pay attentions on 试题答案 在线课程 【答案】A 【解析】 句意:当你穿过马路的时候,你一定注意交通灯。 本句考查动词短语的用法。attention 是不可数名词,选项BD错误;pay attention to…表示对……留心,注意……。是固定短语。所以排除C,选A。
You must the traffic lights when you cross the road. [ ]A.pay attention toB.pay attentions toC.pay attention onD.pay attentions on
In this paper, we propose a novel end-to-end model to jointly learn attentions with semantic cross-modal correlation for efficiently solving the VQA problem. Specifically, we propose a multi-modal embedding to map the visual and question attentions into a joint space to guarantee their semantic ...
In this paper, we propose a novel end-to-end model to jointly learn attentions with semantic cross-modal correlation for efficiently solving the VQA problem. Specifically, we propose a multi-modal embedding to map the visual and question attentions into a joint space to guarantee their semantic ...