重庆工商大学学报（自然科学版）2025，Vol.42Issue(4)：72-79,8.DOI:10.16055/j.issn.1672-058X.2025.0004.009
基于改进YOLOv7的漂浮垃圾目标检测
Floating Garbage Object Detection Based on Improved YOLOv7
摘要
Abstract
Objective In complex inland river environments,most floating garbage consists of small targets that are easily affected by reflections from the water surface and riverbanks.This results in blurred and obstructed target shapes,which poses significant challenges for target detection.To address this issue,this paper proposed an improved YOLOv7-based algorithm for detecting floating garbage in rivers.Methods Firstly,to address the morphological variations of floating garbage in river environments caused by environmental factors,the feature extraction capabilities for small targets were enhanced through the refinement of the SPPCSPC module.Secondly,the centralized feature pyramid was added,which was weighted and fused with the feature pyramid through ROI(region of interest)to facilitate the detection of targets at different scales.Finally,given that traditional Intersection over Union(IoU)is highly sensitive to positional deviations of small targets,which reduces detection performance,IoU was replaced with Wasserstein Distance as the evaluation metric.A loss function based on Normalized Wasserstein Distance(NWD)was implemented to improve detection accuracy.Results The experimental results showed that the accuracy of the improved YOLOv7 algorithm model increased by 3.1％,reaching 89.7％.At IoU=0.5,the average mean precision increased by 6％,reaching 87.8％,and for IoU ranging from 0.5 to 0.95,the average mean precision increased by 4.6％,reaching 43.4％.The detection results of this improved model outperform those of other classical detection models.Conclusion The experimental results indicate that the improved model significantly enhances detection accuracy,providing valuable insights for practical applications.关键词
YOLOv7/小目标检测/EVC Block/SPPCSPC/NWDKey words
YOLOv7/small object detection/EVC block/SPPCSPC/NWD分类
信息技术与安全科学引用本文复制引用
周孟然,范桃春,王宁,蔡睿..基于改进YOLOv7的漂浮垃圾目标检测[J].重庆工商大学学报（自然科学版）,2025,42(4):72-79,8.基金项目
国家重点研发计划重点专项子课题(2018YFC0604503). （2018YFC0604503）
