Estimating Grass Sward Quality and Quantity Parameters Using Drone Remote Sensing with Deep Neural Networks

Estimating Grass Sward Quality and Quantity Parameters Using Drone Remote Sensing with Deep Neural Networks

The objective of this study is to investigate the potential of novel neural network architectures for measuring the quality and quantity parameters of silage grass swards, using drone RGB and hyperspectral images (HSI), and compare the results with the random forest (RF) method and handcrafted featu...

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Bibliographic Details
Main Authors: Kirsi Karila, Raquel Alves Oliveira, Johannes Ek, Jere Kaivosoja, Niko Koivumäki, Panu Korhonen, Oiva Niemeläinen, Laura Nyholm, Roope Näsi, Ilkka Pölönen, Eija Honkavaara
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Remote Sensing
Subjects:
drone
remote sensing
hyperspectral
RGB
CNN
image transformer
Online Access:https://www.mdpi.com/2072-4292/14/11/2692

Internet

https://www.mdpi.com/2072-4292/14/11/2692

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