Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques

Early-Season Stand Count Determination in Corn via Integration of Imagery from Unmanned Aerial Systems (UAS) and Supervised Learning Techniques

Corn (Zea mays L.) is one of the most sensitive crops to planting pattern and early-season uniformity. The most common method to determine number of plants is by visual inspection on the ground but this field activity becomes time-consuming, labor-intensive, biased, and may lead to less profitable d...

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Bibliographic Details
Main Authors: Sebastian Varela, Pruthvidhar Reddy Dhodda, William H. Hsu, P. V. Vara Prasad, Yared Assefa, Nahuel R. Peralta, Terry Griffin, Ajay Sharda, Allison Ferguson, Ignacio A. Ciampitti
Format: Article
Language:English
Published: MDPI AG 2018-02-01
Series:Remote Sensing
Subjects:
unmanned aerial system
supervised learning
corn
farm management
precision agriculture
Online Access:http://www.mdpi.com/2072-4292/10/2/343

Internet

http://www.mdpi.com/2072-4292/10/2/343

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