首页|Southwest University Reports Findings in Robotics (Multi-scale Feature Adaptive Fusion Model for Real-time Detection In Complex Citrus Orchard Environments)
Southwest University Reports Findings in Robotics (Multi-scale Feature Adaptive Fusion Model for Real-time Detection In Complex Citrus Orchard Environments)
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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.
ChongqingPeople’s Republic of ChinaA siaEmerging TechnologiesMachine LearningNano-robotRoboticsSouthwest Un iversity
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