Soil Moisture Estimation Using Hyperspectral Imagery Based on Metric Learning-Reference-Cited by-同舟云学术

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Soil Moisture Estimation Using Hyperspectral Imagery Based on Metric Learning

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA)
language:
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Author:

Tang Bo¹,Xie Weiwei²,Meng Qingmin²,Moorhead Robert J.¹,Feng Gary³

Affiliation:

1. Mississippi State University,Department of Electrical and Computer Engineering,Mississippi State,United States

2. Mississippi State University,Department of Geosciences,Mississippi State,United States

3. USDA-Agricultural Research Service,Mississippi State,United States

Funder

Agricultural Research Service

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10068862/10068777/10069712.pdf?arnumber=10069712

Reference13 articles.

1. Metric learning for kernel regression;weinberger;Artificial Intelligence and Statistics,2007

2. On the Nonparametric Estimation of Regression Functions

3. Gaussian processes in machine learning;rasmussen;Machine Learning Summer School,2003

4. Introducing a Framework of Self-Organizing Maps for Regression of Soil Moisture with Hyperspectral Data

5. The Impacts of Soil Moisture Initialization on the Forecasts of Weather Research and Forecasting Model: A Case Study in Xinjiang, China

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Distributed and Self-powered Soil Monitoring Network for Smart Agriculture;2024 16th International Conference on Computer and Automation Engineering (ICCAE);2024-03-14

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