New approach for predicting nitrogen and pigments in maize from hyperspectral data and machine learning models-Reference-Cited by-同舟云学术

New approach for predicting nitrogen and pigments in maize from hyperspectral data and machine learning models

Published:2024-01 Issue: Volume:33 Page:101110
ISSN:2352-9385
Container-title:Remote Sensing Applications: Society and Environment
language:en
Short-container-title:Remote Sensing Applications: Society and Environment

Author:

Silva Bianca Cavalcante da,Prado Renato de Mello,Baio Fábio Henrique Rojo,Campos Cid Naudi Silva,Teodoro Larissa Pereira Ribeiro,Teodoro Paulo Eduardo,Santana Dthenifer Cordeiro,Fernandes Thiago Feliph Silva,Silva Junior Carlos Antonio da^ORCID,Loureiro Elisangela de Souza

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geography, Planning and Development

Reference78 articles.

1. Random forest regression and spectral band selection for estimating sugarcane leaf nitrogen concentration using EO-1 Hyperion hyperspectral data;Abdel-Rahman;Int. J. Rem. Sens.,2013

2. Machine learning in evaluating multispectral active canopy sensor for prediction of corn leaf nitrogen concentration and yield;Barzin;Rem. Sens.,2021

3. Methods of Chemical Analysis of Plants;Bataglia,1983

4. Random forest in remote sensing: a review of applications and future directions;Belgiu;ISPRS J. Photogrammetry Remote Sens.,2016

5. A random forest guided tour;Biau;Test,2016

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5. Machine Learning in Spectral Imaging for Smart Farming: A Review;2023 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON);2023-12-05