Automated Bale Mapping Using Machine Learning and Photogrammetry

Automated Bale Mapping Using Machine Learning and Photogrammetry

An automatic method of obtaining geographic coordinates of bales using monovision un-crewed aerial vehicle imagery was developed utilizing a data set of 300 images with a 20-megapixel resolution containing a total of 783 labeled bales of corn stover and soybean stubble. The relative performance of i...

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Bibliographic Details
Main Authors: William Yamada, Wei Zhao, Matthew Digman
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Remote Sensing
Subjects:
computer vision
image processing
machine learning
photogrammetry
Online Access:https://www.mdpi.com/2072-4292/13/22/4675

Internet

https://www.mdpi.com/2072-4292/13/22/4675

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