Plant Counting of Cotton from UAS Imagery Using Deep Learning-Based Object Detection Framework

Assessing plant population of cotton is important to make replanting decisions in low plant density areas, prone to yielding penalties. Since the measurement of plant population in the field is labor intensive and subject to error, in this study, a new approach of image-based plant counting is propo...

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Bibliographic Details
Published in:	Remote sensing (Basel, Switzerland) Vol. 12; no. 18; p. 2981
Main Authors:	Oh, Sungchan, Chang, Anjin, Ashapure, Akash, Jung, Jinha, Dube, Nothabo, Maeda, Murilo, Gonzalez, Daniel, Landivar, Juan
Format:	Journal Article
Language:	English
Published:	MDPI AG 01.09.2020
Subjects:	agriculture algorithms automation canopy China cotton data collection detection geometry information labor lighting measurement photogrammetry plant count plant population assessment planting population remote sensing seedlings unmanned aerial vehicles unmanned aircraft systems variability China
ISSN:	2072-4292, 2072-4292
Online Access:	Get full text
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