电子器件2024，Vol.47Issue(4)：1116-1120,5.DOI:10.3969/j.issn.1005-9490.2024.04.037
一种改进YOLOv5积木小零件检测算法研究
Research on an Improved YOLOv5 Algorithm for Detecting Small Parts of Building Blocks
摘要
Abstract
Targeting at the problems of various kinds of building block parts and low manual sorting efficiency,a small part of building block detection algorithm based on improved YOLOv5 is proposed.The algorithm uses double-layer Mosaic-16 for data enhancement and RGB matrix for contrast adjustment.Through the optimization of the dataset,the YOLOv5 algorithm is improved.The experimental re-sults show that the improved YOLOv5 algorithm can quickly and accurately identify and classify small building block parts.Compared with the original YOLOv5 algorithm,the training speed and accuracy of the model are greatly improved.关键词
YOLOv5/积木小零件检测/Mosaic-16增强Key words
YOLOv5/inspection of small building block parts/Mosaic-16 enhancements分类
信息技术与安全科学引用本文复制引用
徐微,郝琦琦,李波波,黄思绒..一种改进YOLOv5积木小零件检测算法研究[J].电子器件,2024,47(4):1116-1120,5.基金项目
陕西省教育科学"十三五"规划2020年度课题项目(SGH20Y1379) （SGH20Y1379）
