To address the aforementioned issues, we propose Global–Local Query-Support Cross-Attention (GLQSCA) for FSS, aiming to fully exploit both local support-query similarities and global prototype-query correlations. As shown in Figure 1, GLQSCA additively aggregates the segmentation label of a quer...
Another local weighting strategy is the attention mechanism. It allows the model to have more direct dependencies between states at different times. Note that the model is used to weigh contextual features and assign different weights to each word. All hidden states are weighted together in the ...
First, even though the Transformer used in GLTF-Net is based on channel-based attention as opposed to window-based attention, it still has higher hardware requirements, which restricts study on thick cloud removal from a wider range of remote sensing images. Second, the synthetic data set used...
This algorithm embeds the self-attention mechanism into the U-net’s bottleneck layer to learn the interdependencies among feature pixels, thereby enhancing the model’s ability to detect anomalies. Wang et al. [31] introduced a multi-path frame prediction network based on the gated circular ...
This algorithm embeds the self-attention mechanism into the U-net’s bottleneck layer to learn the interdependencies among feature pixels, thereby enhancing the model’s ability to detect anomalies. Wang et al. [31] introduced a multi-path frame prediction network based on the gated circular ...
Research on the performance of the frozen soil–concrete interface has received considerable attention. Prior research has indicated that the initial water content, temperature, and surface roughness exert a considerable influence on the interface strength. However, the majority of these studies ...
This algorithm embeds the self-attention mechanism into the U-net’s bottleneck layer to learn the interdependencies among feature pixels, thereby enhancing the model’s ability to detect anomalies. Wang et al. [31] introduced a multi-path frame prediction network based on the gated circular ...
where 𝒞𝑚Cm is the channel attention operation. 𝜃𝑐θc denotes the assigning of a separate parameter to each feature. To learn the spatial shift between modalities from the guided subspace as a strong prior for subsequent alignment and fusion, we use deformable convolutions to achieve im...
few-shot image generation; power scenarios; self-attention encoder; multi-view feature fusion 1. Introduction The significance of defect detection in power equipment is crucial for the safety and stable development of both a country and society at large. With the emergence of the Internet of ...
extracting local and global features, respectively, making them well-suited for capturing the local features of drugs and the global features of targets. By combining these with a shared attention mechanism and sparse feature selection, the predictive performance of the model can be significantly ...