2.1Multi-scale attention maps 网络基于resnet101的修改,res2-res5层输出的不同尺度特征图定义为F0,F1,F2,F3,将他们上采样到统一的尺度得到 ,将 在通道上堆叠经过卷积得到 (多尺度特征图). 得到的多尺度特征图 再分别和 进行concatenate操作,经过卷积后送入到Guided Attention模块中,得到注意力特征图(attention ...
In this paper, we first propose a multi-scale channel attention network with an adaptive feature fusion strategy (MSCAN-AFF) for face recognition (FR), which fuses the relevant feature channels and improves the network's representational power. In FR, face alignment is performed independently ...
利用数据集中的所有单词会对精度产生负面影响,这说明低频单词会对模型产生噪声,同样bi-LSTM更加有效率。 下表展示了在视觉CNN (Con-pose)、粗糙对齐网络(CA)和细粒度对齐网络(FA)之前连接位姿置信度图的有效性。 具体来说,将姿态置信度图与原始输入图像连接确实提高了匹配性能,这说明姿态信息在学习有区别的人类相关...
"'Multi-scale self-guided attention for medical image segmentation'", which has been recently accepted at the Journal of Biomedical And Health Informatics (JBHI). Abstract Even though convolutional neural networks (CNNs) are driving progress in medical image segmentation, standard models still have ...
code:GitHub - sinAshish/Multi-Scale-Attention: Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation" 问题的提出:信息流的冗余使用(低层次的特征被多次提取) 在使用引导性自我注意机制的基础上,捕捉更丰富的上下文依赖关系。这种方法能够将局部特征与它们相应的全局依赖关系结合起来,并...
MEGANet: Multi-Scale Edge-Guided Attention Network for Weak Boundary Polyp Segmentation (WACV 2024) Nhat-Tan Bui·Dinh-Hieu Hoang·Quang-Thuc Nguyen·Minh-Triet Tran.Ngan Le arXiv.open access Introduction Efficient polyp segmentation in healthcare plays a critical role in enabling early diagnosis ...
Electroencephalography (EEG)-based emotion recognition has gained widespread attention recently. Although many deep learning methods have been proposed, it is still challenging to simultaneously fuse information in the time–frequency–spatial domain. This paper proposes an attention mechanism-guided dual-...
医学分割论文:Multi-scale guided attention for medical image segmentation,程序员大本营,技术文章内容聚合第一站。
原文:Multi-Channel Attention Selection GANs for Guided Image-to-Image Translation 摘要 我们提出了一种名为多通道注意选择生成对抗网络(SelectionGAN)的新颖模型,用于引导图像到图像的翻译,在该模型中,我们将输入图像转换为另一图像,同时尊重外部语义指导。 所提出的 SelectionGAN 明确利用了语义指导信息,并由两个...
Drawing on the human cognitive process, this paper proposes a novel structure for multi-scale rotated ship detection called the Feature Attention Transfer module, which generates and transfers attention in multi-level feature maps to instruct each prediction branch to focus on the features that are ...