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Cloud Detection and Tracking Based on Object Detection with Convolutional Neural Networks.

Authors :
Carballo, Jose Antonio
Bonilla, Javier
Fernández-Reche, Jesús
Nouri, Bijan
Avila-Marin, Antonio
Fabel, Yann
Alarcón-Padilla, Diego-César
Source :
Algorithms; Oct2023, Vol. 16 Issue 10, p487, 13p
Publication Year :
2023

Abstract

Due to the need to know the availability of solar resources for the solar renewable technologies in advance, this paper presents a new methodology based on computer vision and the object detection technique that uses convolutional neural networks (EfficientDet-D2 model) to detect clouds in image series. This methodology also calculates the speed and direction of cloud motion, which allows the prediction of transients in the available solar radiation due to clouds. The convolutional neural network model retraining and validation process finished successfully, which gave accurate cloud detection results in the test. Also, during the test, the estimation of the remaining time for a transient due to a cloud was accurate, mainly due to the precise cloud detection and the accuracy of the remaining time algorithm. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19994893
Volume :
16
Issue :
10
Database :
Complementary Index
Journal :
Algorithms
Publication Type :
Academic Journal
Accession number :
173265538
Full Text :
https://doi.org/10.3390/a16100487