计算机与数字工程2024，Vol.52Issue(12)：3703-3709,7.DOI:10.3969/j.issn.1672-9722.2024.12.039
基于柔性跨层连接和自注意力机制的道路检测方法
Road Detection Method Based on Soft Cross-layer Connection and Self Attention
摘要
Abstract
Self attention is one of the important methods to improve the accuracy of road detection.Compared with attention mechanism,self attention reduces the dependence on external information and makes it have stronger data capture ability.When cal-culating the response between two locations,Non-local network will consider the weight of all dimensional feature graphs,but the amount of calculation will increase.SENet obtains the weight matrix with global receptive field through extrusion and excitation,but the fitting ability of SENet to road edge is limited.A new self attention module is designed to compress the information in different di-mensions by convolution and matrix multiplication without increasing too much computation,so as to obtain more global informa-tion.Flexible cross layer connection is introduced between encoder and decoder to improve network performance.In terms of loss function,BCD(Bray Curtis distance)and hinge loss are introduced based on the common cross entropy loss function.By giving higher punishment to the wrong points near the road edge,the network has the ability to better fit the road edge.Experiments show that the detection accuracy of this method is higher than that of Non-local net and SENet.关键词
自注意力/道路检测/特征图/柔性跨层连接Key words
self attention/road detection/feature map/soft cross-layer分类
信息技术与安全科学引用本文复制引用
金鑫,陈雪云..基于柔性跨层连接和自注意力机制的道路检测方法[J].计算机与数字工程,2024,52(12):3703-3709,7.基金项目
国家自然科学基金项目"城市遥感图像中机动目标及其周边环境属性的解耦检测研究"(编号:62061002)资助. （编号:62061002）
