Lightweight detection networks for tea bud on complex agricultural environment via improved YOLO v4
Author:
Publisher
Elsevier BV
Subject
Horticulture,Computer Science Applications,Agronomy and Crop Science,Forestry
Reference31 articles.
1. Hormonal regulation of health-promoting compounds in tea (Camellia sinensis L.);Ahammed;Plant Physiol. Biochem.,2022
2. YOLOv4: Optimal speed and accuracy of object detection;Bochkovskiy,2020
3. Lightweight tea bud recognition network integrating GhostNet and YOLOv5;Cao;Math. Biosci. Eng.,2022
4. Localizing plucking points of tea leaves using deep convolutional neural networks;Chen;Comput. Electron. Agric.,2020
5. Adaptive neural network control of AUVs with control input nonlinearities using reinforcement learning;Cui;IEEE Trans. Syst. Man Cybern.,2017
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