计算机与数字工程2026，Vol.54Issue(6)：1575-1579,1624,6.DOI:10.3969/j.issn.1672-9722.2026.06.006
基于CycleGAN以及改进YOLOv5的垃圾检测算法
Garbage Detection Algorithm Based on CycleGAN and Improved YOLOv5
赵和月 1何利文1
作者信息
- 1. 南京邮电大学物联网学院 南京 210003
- 折叠
摘要
Abstract
Garbage classification has been a hot topic since 2019,and it is of great significance to reasonably classify domes-tic garbage through artificial intelligence algorithms.Since the development of artificial intelligence,from traditional machine learn-ing to the current deep learning,both the recognition speed and recognition efficiency have been greatly improved.In order to solve the problem of insufficient datasets at night and improve the recognition rate of garbage detection,data enhancement is carried out based on CycleGAN,and the YOLOv5 model is improved.The experimental results show that after using CycleGAN data enhance-ment,mAP increases from 0.795 to 0.864,an increase of 6.9%,and after improving YOLOv5,mAP increases from 0.864 to 0.903,achieving an increase of 3.9%.关键词
垃圾分类/深度学习/YOLOv5/CycleGAN/数据增强/目标检测Key words
garbage classification/deep learning/YOLOv5/CycleGAN/data augmentation/target detection分类
信息技术与安全科学引用本文复制引用
赵和月,何利文..基于CycleGAN以及改进YOLOv5的垃圾检测算法[J].计算机与数字工程,2026,54(6):1575-1579,1624,6.
