Convolutional neural networkMulti-scale attention mechanismWith the rapid increase of data availability, time series classification (TSC) has arisen in a wide range of fields and drawn great attention of researchers. Recently, hundreds of TSC approaches have been developed, which can be classified ...
To address this concern, we introduce EMCAD, a new efficient multi-scale convolutional attention decoder, designed to optimize both performance and computational efficiency. EMCAD leverages a unique multi-scale depth-wise convolution block, significantly enhancing feature maps through multi-scale convolution...
效率方面,Mss-AGCN以1.74M参数量与2.22G FLOPs的计算开销显著优于主流模型(如MS-G3D的6.4M/48.98G),其多尺度采样策略将自注意力复杂度从O(N2)降至O(kN)(k≪N),验证了轻量化设计的有效性。消融实验进一步表明,AGCN模块相比纯GCN或MHSA提升1.1%~1.8%,LFS/GFS策略相比固定邻域采样(如SCP)提升0.48%~1.03%,...
SCA-CNN: Spatial and Channel-wise attention in convolutional networks for image... Christian, S., Vincent, V., Sergey, I., Jonathon, S., Zbigniew, W., 2016. Rethinking the inception architecture for... Christian, S., Wei, L., Yangqing, J., Pierre, S., 2015. Going deeper with ...
Liyun Su, Lang Xiong和Jialing Yang在2024年发表了题为“Multi-Attn BLS: Multi-head attention mechanism with broad learning system for chaotic time series prediction”的论文,发表在《Applied Soft Computing》杂志上(CiteScore14.3,影响因子8.7)。这篇论文针对混沌时间序列数据的高复杂性和非线性提出了一种新的...
Technically, the MSCCA is developed in terms of self-attention learning linearly on the channels. Due to the one-by-one relationship between the channels and the convolutional filters, the MSCCA measures actually the importance of multi-scale feature maps at the level of feature extractor. In ...
论文题目:Multi-scale sampling attention graph convolutional networks for skeleton-based action recognition 作者&团队:Tian H, Zhang Y, Wu H, et al. 1.山东大学控制科学与工程学院机器人中心2.加州大学洛杉矶分校电气与计算机工程系 发表期刊/会议:Neurocomputing 中科院分区:SCI2区 年份、卷号、刊号、页码:202...
Multi-Attention Convolutional Network笔记 此篇文章记录自己对2017年的ICCV一篇关于图像领域的注意力模型的理解。(论文题目《Learning Multi-Attention Convolutional Neural Network for Fine-Grained Image Recognition》) Approach 整个结构由三部分组成,分别是特征提取的卷积层、channel grouping层和part classifier ......
Multi-scale Convolutional Neural Network with Channel Attention (CA-MCNN) is proposed in this paper. In CA-MCNN, the maximum pooling and average pooling layers are used to extract the multi-scale information of the bearing signals, which increases the dimensions of input. The channel attention ...
Local climate zone Scene classification Multi-scale multi-level attention Convolutional block attention module Context aggregation Remote sensing Urban climate 1. Introduction More than half of the world’s population currently live in urban areas and the United Nations (UN) projects this estimate to es...