Attention mechanismTo detect the targets of different sizes, multi-scale output is used by target detectors such as YOLO V3 and DSSD. To improve the detection performance, YOLO V3 and DSSD perform feature fusion by combining two adjacent scales. However, the feature fusion only between the ...
Specifically, we propose a Multi-Scale Adaptive Spatial Attention Gate (MASAG), which dynamically adjusts the receptive field (Local and Global contextual information) to ensure that spatially relevant features are selectively highlighted while minimizing background distractions. Extensive evaluations ...
该预测部分由两个系列计算组成,首先先计算基本部分: 作者先提取了每层 Attention 的权重,也就是最后乘 V 之前,之后由于是 Multi-head,为了保留所有特征,方法选取将每个端口的权重图相乘: L 为层数;K 为 Multi-head 数量;C 为通道数;这公式着实写的不是很精致 之后将这些 A 连接在一起,大小就为 L*N,即下...
Afterward, label-aware local features of Q&As are constructed through the attention mechanism and fused with Q&A global features using the multi-head self-attention to establish the multi-scale fusion classification features of Q&As. Then, to extract the core multi-scale fusion features, a multi-...
Moreover, we design a multi-scale attention mechanism to aggregate information from multiple ranges, which makes the graph convolution focus on more efficient nodes, frames, and channels. To further improve the performance of the model, a novel multi-stream framework is proposed to aggregate the ...
To address these issues, the authors propose a novel adaptive attention that enhances features through the spatial sparse attention mechanism with less than 1/4 of the computational complexity of multi-head attention. Our adaptive attention sets a perception range around each element in the feature ...
1,集成了H.265标准参考软件HM的拟议高效视频编码系统(EVCS)可以实现12.141%的比特率节省,其性能优于基于深度学习的压缩视频恢复工作。 此外,EVCS可以轻松地与所有现有视频编解码器兼容,而无需修改其内核。 2,我们提出了多尺度通道注意(MSCA)机制,以提取不同尺度的特征并通过考虑特征通道之间的相关性来自适应地重新缩...
Kernel Attention Based Multi-scale Adaptive Graph Convolutional Neural Network for Skeleton-Based doi:10.1109/ICVR51878.2021.9483811Training,Adaptation models,Solid modeling,Adaptive systems,Correlation,Fuses,Virtual realityGraph convolution network is widely used in skeleton-based action recognition tasks. To ...
adaptive graph attention mechanism, incorporates geometry structure including angle, distance, and multiscale curvature, long-range molecular interactions, and heterophily of the graph into the protein-ligand complex representation. We demonstrate the superiority of our proposed model through experiments ...
A deep learning approach to state of charge estimation of lithium-ion batteries based on dual-stage attention mechanism 2022, Energy Citation Excerpt : The most obvious shortcoming of the ampere-hour integration method is that only the current calculation will lead to the accumulation of errors, wi...