Estimates of Maize Plant Density from UAV RGB Images Using Faster-RCNN Detection Model: Impact of the Spatial Resolution
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Open Access
- 1 January 2021
- journal article
- research article
- Published by American Association for the Advancement of Science (AAAS) in Plant Phenomics
Abstract
Early-stage plant density is an essential trait that determines the fate of a genotype under given environmental conditions and management practices. The use of RGB images taken from UAVs may replace the traditional visual counting in fields with improved throughput, accuracy, and access to plant localization. However, high-resolution images are required to detect the small plants present at the early stages. This study explores the impact of image ground sampling distance (GSD) on the performances of maize plant detection at three-to-five leaves stage using Faster-RCNN object detection algorithm. Data collected at high resolution () over six contrasted sites were used for model training. Two additional sites with images acquired both at high and low (Keywords
Funding Information
- ANRT
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