Research on Lightweight Citrus Flowering Rate Statistical Model Combined with Anchor Frame Clustering Optimization

At present, learning-based citrus blossom recognition models based on deep learning are highly complicated and have a large number of parameters. In order to estimate citrus flower quantities in natural orchards, this study proposes a lightweight citrus flower recognition model based on improved YOL...

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Veröffentlicht in:	Sensors (Basel, Switzerland) Switzerland), 2021-11, Vol.21 (23), p.7929
Hauptverfasser:	Lu, Jianqiang, Lin, Weize, Chen, Pingfu, Lan, Yubin, Deng, Xiaoling, Niu, Hongyu, Mo, Jiawei, Li, Jiaxing, Luo, Shengfu
Format:	Artikel
Sprache:	eng
Schlagworte:	Acceleration Accuracy Algorithms citrus flowering rate Clustering Data collection Datasets Deep learning edge computing Edge detection Flowering Flowers & plants light weight Lightweight Methods Neural networks Orchards Recognition Statistical models YOLOv4
Online-Zugang:	Volltext
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