计算机与数字工程2023，Vol.51Issue(12)：2831-2835,3027,6.DOI:10.3969/j.issn.1672-9722.2023.12.012
一种适用于轻量级网络的双分支融合注意力机制
A Dual-branch Fusion Attention Mechanism for Lightweight Networks
摘要
Abstract
The attention mechanism attracts more and more attention.Many studies respectively proved the effectiveness of channel attention and spatial attention in improving model performance.However,existing algorithms usually ignore how to well combine these two kinds of information.In this regard,by effectively combining channel attention,spatial attention,and feature in-formation extracted globally,a new attention mechanism for mobile networks called dual-branch fusion attention is proposed,and is applied to several classic lightweight networks for experimentation.The experimental results show that the accuracy of the model in-troduced with the dual-branch fusion attention mechanism is obviously higher than that of the original model on the CIFAR-100 and ImageNet-100 datasets,and the amount of floating-point calculations and the model volume do not increase significantly.关键词
轻量级网络/注意力机制/双分支融合Key words
lightweight network/attention mechanism/double branch fusion分类
数理科学引用本文复制引用
邓宇晗,阳富民,袁凌,胡贯荣..一种适用于轻量级网络的双分支融合注意力机制[J].计算机与数字工程,2023,51(12):2831-2835,3027,6.基金项目
国家自然科学基金项目(编号:62272180)资助. （编号:62272180）
