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- 저자 : Zhai Danlan (검색결과 1 건)
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Evaluation of the YOLO models for discrimination of the alfalfa pollinating bee species
Zhang Chuan-Jie,Liu Teng,Wang Jinxu,Zhai Danlan,Zhang Youxin,Gao Yang,Wu Hui-Zhen,Yu Jialin,Chen Min 한국응용곤충학회 2024 Journal of Asia-Pacific Entomology Vol.27 No.1
Identifying insect pollinators and their roles in mediating pollen flow is critical to understand the potential gene flow risks of insect pollination-dependent crop species, such as alfalfa. This study was conducted to evaluate and compare the feasibility of You Only Look Once (YOLO) version 3 (YOLOv3), YOLOv5, YOLOv7, and YOLO Representation (YOLOR) to discriminate the three most common alfalfa pollinating bee species, including honeybee, bumblebee, and leafcutting bee. The metrics comparison results showed YOLOv3 and YOLOv5 out performed YOLOv7 and YOLOR regarding model precision, recall, F 1 score, and mAP50 values. YOLOv3 and YOLOv5 could successfully discriminate the three different bee species with an accuracy of almost 100% (99.9%, 99.8%, and 100% accuracy for honeybee, bumblebee, and leafcutting bee for the two models, respectively). Comparatively, YOLOv7 could discriminate honeybee with an accuracy of 95% but was more likely to mistakenly discriminate bumblebee and leafcutting bee due to the relatively lower discriminating accuracy (87.3% and 66.2%, respectively). While the values of determined parameters for YOLOR were lower than YOLOv3 and YOLOv5, the higher precision (0.99680) along with recall (0.98721), F 1 (0.99198), mAP50 (0.99323), and mAP50-100 (0.89076) values indicate that this model could be able to obtain a favorable performance in discriminating the three bee species. In summary, the proposed method in this study has the potential for identifying the alfalfa pollinating bee species, studying the bees’ flower-visiting behaviors, evaluating the risks of insect-mediated pollen flow, and thus contributing to the management of genetically engineered (GE) alfalfa transgene flow.
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