作者提出的方法叫做 Multi-scale Attention Network(MAN),总体框架如下图所示。核心模块为MAB,是一个 Transformer block,由 attention 和 FFN 组成。其中,attention 为 MLKA,FFN 为 GSAU。需要注意的是,最后还使用了一个LKAT,下面分别进行详细介绍。 1、Multi-scale Large Kernel Attention (MLKA) MLKA首先使用 ...
核心模块为MAB,是一个 Transformer block,由attention和 FFN 组成。其中,attention 为 MLKA,FFN 为 GSAU。需要注意的是,最后还使用了一个LKAT,下面分别进行详细介绍。 1、Multi-scale Large Kernel Attention (MLKA) MLKA首先使用 Point-wise conv 改变通道数,然后将特征 split 成三组,每个组都使用 VAN 里提出...
In this section, we describe the proposed method in detail including Res-block, Position-wise Attention Block and Multi-scale Fusion Attention Block. We adopt the improved encoder-decoder architecture of U-Net for liver and tumors segmentation in the paper. The Res-block consists of three 3×3...
解决方法:全连接的self-attention改为不同layer不同head各自按不同scale进行连接从而削减参数量。如下图所示,scale反应的是attention计算的时候,两个位置在序列中的距离 (图来自邱博的ppt,侵删) 为什么敢这么做是因为bert模型attention权重的统计结果,发现大部分虽然建立了全部连接但是,大部分知识都是从近距离获取而来,...
attention的query是经过两个ConvStep再做一次self-attention(self-attention参见[5])得到,attention的key...
Coronavirus 2019 (COVID-19) is a new acute respiratory disease that has spread rapidly throughout the world. In this paper, a lightweight convolutional neural network (CNN) model named multi-scale gated multi-head attention depthwise separable CNN (MGMAD
To efficiently balance model complexity and performance, we propose a multi-scale attention network (MSAN) by cascading multiple multi-scale attention blocks (MSAB), each of which integrates a multi-scale cross block (MSCB) and a multi-path wide-activated attention block (MWAB). Specifically, ...
【YOLOv8改进】EMA(Efficient Multi-Scale Attention):基于跨空间学习的高效多尺度注意力 (论文笔记+引入代码) 简介:YOLO目标检测专栏介绍了创新的多尺度注意力模块EMA,它强化通道和空间信息处理,同时降低计算负担。EMA模块通过通道重塑和并行子网络优化特征表示,增强长距离依赖建模,在保持效率的同时提升模型性能。适用于...
每一层是一个Transformer block(块)。在每个块内,前面是一个Multi-Head Attention多头注意力,后面接...
Therefore, we investigate a novel end-to-end model based on deep learning named as Multi-scale Attention Convolutional Neural Network (MACNN) to solve the TSC problem. We first apply the multi-scale convolution to capture different scales of information along the time axis by generating different...