摘要
机器人与机器学习每日新闻的一位新闻记者兼新闻编辑-目前关于机器人的研究结果已经公布。根据NewsRx记者在中华人民共和国武汉发布的新闻报道，研究表明：“目前的苹果检测算法HMS无法准确区分模糊苹果和可摘苹果，导致苹果收获准确率低，应用程序LES被错误采摘或完全遗漏的情况发生率高。为了解决现有算法存在的问题，本研究提出了一种改进的YOLOv5s-based实时苹果检测方法YOLOv5s-BC,该方法引入了一系列改进。本研究的资助机构包括武汉理工大学国家创新与创业培训项目。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Current study results on Robotics have been publi shed. According to news reporting originating in Wuhan, People’s Republic of Chi na, by NewsRx journalists, research stated, “The current apple detection algorit hms fail to accurately differentiate obscured apples from pickable ones, thus le ading to low accuracy in apple harvesting and a high rate of instances where app les are either mispicked or missed altogether. To address the issues associated with the existing algorithms, this study proposes an improved YOLOv5s-based meth od, named YOLOv5s-BC, for real-time apple detection, in which a series of modifi cations have been introduced.” Financial supporters for this research include Wuhan University of Technology, N ational Innovation and Entrepreneurship Training Program for College Students.
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