Although many different vascular segmentation techniques have already been presented, additional study is still required to address the problem of inadequate segmentation of thin and tiny vessels.#In this work, we introduce the Spatial Attention U-Net (SAU-Net) modelwith harris hawks' optimization (...
In this work, we propose a lightweight network named Spatial Attention U-Net (SA-UNet) that does not require thousands of annotated training samples and can be utilized in a data augmentation manner to use the available annotated samples more efficiently. SA-UNet introduces a spatial attention ...
To address the above complex problems, we propose an encoder–decoder network, namely, DSMSA-Net, integrated with attention units to cope with road segmentation tasks in high spatial resolution satellite images. The encoder part of the network extracts multi-scale features from different convolutional...
理论上讲ST是可以以任意数量插入到网络中的任意位置,ST可以起到裁剪的作用,是一种高级的Attention机制。但多个ST无疑增加了网络的深度,其带来的收益价值值得讨论; STM虽然可以起到降采样的作用,但一般不这么使用,因为基于ST的降采样产生了对其的问题; 可以在同一个卷积网络中并行使用多个ST,但是一般ST和图像中的对...
5). The possible reasons are: (1) UHI has a smaller spatial extent in developing countries as their urbanization level is still low; (2) UHI impacts were not paid enough attention in developing countries as the governments focused more on socioeconomic development instead of the environment; ...
EDR-TransUnet: Integrating Enhanced Dual Relation-Attention With Transformer U-Net for Multiscale Rock Segmentation on Mars By integrating global and local features, image-specific positional and channel features, and using the Transformer and EDR-Block, the performance of rock ... Y Jia,G Wan,W...
aiming to integrate theTransformer and dual attention block(DA-Block) into the traditional U-shaped architecture. Unlikeearlier transformer-based U-net models, DA-TransUNet utilizes Transformers and DA-Block tointegrate not only global and local features, but also image-specif ic positional and channe...
we aim to propose a novel attention mechanism by taking into account the two factors: For the first factor, inspired by the CapsuleNet [11] where the grouped sub-features can represent the instantiation parameters of a specific type of en- tity, we propose a group-...
The ability to predict the prognosis of patients with ovarian cancer can greatly improve disease management. However, the knowledge on the mechanism of the prediction is limited. We sought to deconvolute the attention feature learnt by a deep learning co
A third epoch began when investigators turned their attention to the entorhinal cortex, which led to the discovery of grid cells and border cells. This review will show how ideas about integration of self-motion cues have shaped our understanding of spatial representation in hippocampal–entorhinal ...