Hybrid Deep Neural Networks with Multi-Tasking for Rice Yield Prediction Using Remote Sensing Data

Recently, data-driven approaches have become the dominant solution for prediction problems in agricultural industries. Several deep learning models have been applied to crop yield prediction in smart farming. In this paper, we proposed an efficient hybrid deep learning model that coordinates the out...

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Bibliografische gegevens
Hoofdauteurs:	Che-Hao Chang, Jason Lin, Jia-Wei Chang, Yu-Shun Huang, Ming-Hsin Lai, Yen-Jen Chang
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2024-03-01
Reeks:	Agriculture
Onderwerpen:	crop yield prediction remote sensing convolutional neural network deep learning multi-task learning
Online toegang:	https://www.mdpi.com/2077-0472/14/4/513
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Hybrid Deep Neural Networks with Multi-Tasking for Rice Yield Prediction Using Remote Sensing Data

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