Calibrating UAV thermal sensors using machine learning methods for improved accuracy in agricultural applications-Reference-Cited by-同舟云学术

Calibrating UAV thermal sensors using machine learning methods for improved accuracy in agricultural applications

Published:2023-09 Issue: Volume:133 Page:104804
ISSN:1350-4495
Container-title:Infrared Physics & Technology
language:en
Short-container-title:Infrared Physics & Technology

Author:

Tunca Emre^ORCID,Köksal Eyüp Selim,Çetin Taner Sakine

Funder

Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

European Cooperation in Science and Technology

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference49 articles.

1. Simplified Evaluation of Cotton Water Stress Using High Resolution Unmanned Aerial Vehicle Thermal Imagery;Bian;Remote Sens-Basel,2019

2. FAO, Water for Sustainable Food and Agriculture, (2017).

3. Operational Precise Irrigation for Cotton Cultivation through the Coupling of Meteorological and Crop Growth Models;Tsakmakis;Water Resour. Manag.,2017

4. IEEE India Geoscience and Remote Sensing Symposium (InGARSS);Das;IEEE,2020

5. Comparative Evaluation of Land Surface Temperature Images from Unmanned Aerial Vehicle and Satellite Observation for Agricultural Areas Using In Situ Data;Awais;Agriculture-Basel,2022

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