现代电子技术2025，Vol.48Issue(5)：59-67,9.DOI:10.16652/j.issn.1004-373x.2025.05.010
并行池化注意力及多特征融合增强目标检测方法
Object detection method based on parallel pooling of attention and multi-feature fusion enhancement
摘要
Abstract
A parallel pooling of attention and multi-feature fusion enhancement(PPA-MfFE)method is proposed to get rid of the detail information loss and inadequate feature fusion caused by channel attention dimension reduction.Firstly,two pooling modules are used to process the input image in parallel to enhance the feature attention.In the entropy-guided pooling module,the channel information entropy is used to generate the feature weight coefficient and enhance the detailed information of edge texture.The directional awareness pooling module is responsible for capturing the spatial direction information of the image in both vertical and horizontal directions.And then,the channel mean is calculated,so as to achieve gradual dimensionality reduction and retain the key features.Secondly,the multi-feature fusion enhancement module is used to select the size of the convolution kernel adaptively by the logarithmic function of the feature graph scale,and reshape the convolution feature group into three feature subgraphs in the directions of channel,height and width with the same dimension as the input image,and then multiply the elements to obtain the enhanced feature graph.Finally,the enhanced feature graph is weighted and fused with the input image to enhance the location and detail information of the object.Experimental results show that,with the same number of parameters,the mAP@0.5 of the proposed algorithm is 4.62% and 4.46% higher than those of YOLOX and YOLOv7 in VOC2007 dataset,respectively,and its mAP@0.5 is 4.57% and 4.63% higher than those of YOLOX and YOLOv7 in COCO dataset,respectively.关键词
通道注意力/降维/并行池化/多特征融合增强/自适应/目标检测Key words
channel attention/dimensionality reduction/parallel pooling/multi-feature fusion enhancement/self-adaptation/object detection分类
电子信息工程引用本文复制引用
程杰,卞长智,张婧,李小霞,丁楠..并行池化注意力及多特征融合增强目标检测方法[J].现代电子技术,2025,48(5):59-67,9.基金项目
国家自然科学基金面上项目(62071399) （62071399）
四川省科技计划重点研发项目(2023YFG0262,2023NSFSC1388) （2023YFG0262,2023NSFSC1388）
