注意力机制在医学图像分割领域的应用是近年来研究的热点。Attention U-Net论文为这一领域带来了新的视角，提出将软注意力的思想引入医学图像中。该论文在医学图像分析领域发表，并得到了广泛引用。注意力机制分为硬注意力和软注意力。硬注意力一次选择图像的特定区域作为关注焦点，将其设为1，其他区域设为...
Attention U-Net是一种带有Soft Attention的Unet结构,通过深层feature监督浅层feature实现Attention机制 提出一种Attention Gate的注意力机制,结构如图所示: 如图所示Attention Gate作用在下采样的特征图上。在使用skip connection之前,通过下采样的特征图x与上采样的特征图g得到注意力权重,作用于下采样特征图x,最后将下...
论文阅读——Attention U-Net: Learning Where to Look for the Pancreas,程序员大本营,技术文章内容聚合第一站。
In this paper, we propose an attention guided U-Net with atrous convolution(AA-UNet), which guides the model to separate vessel and non-vessel pixels and reuses deep features. Firstly, AA-UNet regresses a boundary box to the retinal region to generate an attention mask, which was used as ...
研究了利用CT图像对肝脏肿瘤区域进行自动分割,提出一种新的深度神经网络Attention-ResUNet.该网络重新设计U-Net的编解码结构,在特征提取模块中结合残差模块来加强了特征映射,并利用通道注意力机制和空间注意力机制对特征重新标定,增强有效特征,使得特征能够高效传输.实验表明,Attention-ResUNet在3D-IRCADb数据集和LiTS数...
First, for encoder-decoder architectures such as U-Net, the utilization of multi-scale features causes the overuse of information, where similar low-level features are exploited at multiple scales over multiple times. Second, long-range dependencies of feature maps are not sufficiently explored, ...
Channel-wise Attention: 作者是从Semantic Attention的思想转换过来的, 这在related work中没发现较早应用. 之后的SE-net都是引用该文章的. SCA额外添加的参数量很大, SE-net论文中说: 相比SCA_CNN, SE_net是轻量级且专注于对channel建模的机制. SCA-CNN: Spatial and Channel-wise Attention in Convolutional Ne...
セマンティクスセグメンテーションのベースラインである F-CNN ベースのアーキテクチャ(U-Net など)では、小さな物体や領域でのセグメンテーション品質が悪いという問題が存在する。 既存のセグメンテーションモデルである PSPNet では、この問題に対処するために spatial pyramid pooling と...
Our method can be used with any semantic segmentation model, such as U-Net, PSP-Net, etc. Taking PSP-Net as an example, its basic structure is shown in Figure 1 [22]. The input image (a) is fed into a Convolutional Neural Network (CNN) to obtain the feature map of the last convo...
Compared with U-Net, HEU-Net achieves a 7.91% improvement in F1 and a 10.16% improvement in mIoU. These results show that our method outperforms state-of-the-art models and can achieve better semantic segmentation results. 展开 关键词: Corrosion detection Semantic segmentation Attention Residual ...