Hyper-Parameter Optimization-based multi-source fusion for remote sensing inversion of non-photosensitive water quality parameters-Reference-Cited by-同舟云学术

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Hyper-Parameter Optimization-based multi-source fusion for remote sensing inversion of non-photosensitive water quality parameters

Published:2024-09-08 Issue:18 Volume:45 Page:6838-6859
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Yuan Yuhao¹,Lin Zhiping¹,Jiang Xinhao¹,Fan Zhongmou¹^ORCID

Affiliation:

1. School of Transportation and Civil Engineering, Fujian Agriculture and Forestry University, Fuzhou, China

Funder

Ministry of Science and Technology

National Natural Science Foundation of China

Fujian Provincial Department of Science and Technology

Natural Science Foundation of Fujian Province

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2024.2388878

Reference56 articles.

1. Random forest in remote sensing: A review of applications and future directions

2. Remote sensing inversion of water quality parameters in the Yellow River Delta

3. LASSO (L1) Regularization for Development of Sparse Remote-Sensing Models with Applications in Optically Complex Waters Using GEE Tools

4. Machine learning-based inversion of water quality parameters in typical reach of the urban river by UAV multispectral data

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