Robotics & Machine Learning Daily News2024,Issue(MAY.31) :23-24.

Southwest University Reports Findings in Robotics (Multi-scale Feature Adaptive Fusion Model for Real-time Detection In Complex Citrus Orchard Environments)

Robotics & Machine Learning Daily News2024,Issue(MAY.31) :23-24.

Southwest University Reports Findings in Robotics (Multi-scale Feature Adaptive Fusion Model for Real-time Detection In Complex Citrus Orchard Environments)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Robotics is now availab le. According to news reporting originating from Chongqing, People’s Republic of China, by NewsRx correspondents, research stated, “A Multi - scale Feature Adapt ive Fusion model (MFAF-YOLO) for real-time detection of citrus harvesting robots in complex field environments is proposed in this study. This proposed model im proves detection accuracy while meeting the lightweight requirements of consumer -level cameras.” Financial supporters for this research include Science Fund for Distinguished Yo ung Scholars of Chongqing Municipality, Shuangcheng cooperative agreement resear ch grant of Yibin, China, Fundamental Research Funds for the Central Universitie s, Chongqing Graduate Student Research Innovation Project.

Key words

Chongqing/People’s Republic of China/A sia/Emerging Technologies/Machine Learning/Nano-robot/Robotics/Southwest Un iversity

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文