Detecting and Mapping Individual Fruit Trees in Complex Natural Environments via UAV Remote Sensing and Optimized YOLOv5

Detecting and Mapping Individual Fruit Trees in Complex Natural Environments via UAV Remote Sensing and Optimized YOLOv5

The location and number of individual fruit trees (IFTs) are critical for investigations on planting areas, fruit yield predictions, and smart orchard planning and management. These data are conventionally obtained through manual and statistical investigations that require long, laborious, and costl...

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Bibliographic Details
Main Authors: Yongzhu Xiong, Xiaofeng Zeng, Weiqian Lai, Jiawen Liao, Yankui Chen, Mingyong Zhu, Kekun Huang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning
individual tree detection
remote sensing
spatial distribution
unmanned aerial vehicle (UAV)
Online Access:https://ieeexplore.ieee.org/document/10478285/

Internet

https://ieeexplore.ieee.org/document/10478285/

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