Soil Moisture Estimation From Smap Observations Using Long Short- Term Memory (LSTM)-Reference-Cited by-同舟云学术

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Soil Moisture Estimation From Smap Observations Using Long Short- Term Memory (LSTM)

Published:2019-07 Issue: Volume: Page:
ISSN:
Container-title:IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Abbes Ali Ben,Magagi Ramata,Goita Kalifa

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8891871/8897702/08898418.pdf?arnumber=8898418

Cited by 13 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. Advances in remote sensing based soil moisture retrieval: applications, techniques, scales and challenges for combining machine learning and physical models;Artificial Intelligence Review;2024-08-02

2. Soil Moisture Retrieval Using in Situ and Data Simulation Regularized Deep Learning Models;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

3. Design, Fabrication, and Implementation of an Agriculture robot;2022 10th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO);2022-10-13

4. Retrieval of Farmland Surface Soil Moisture Based on Feature Optimization and Machine Learning;Remote Sensing;2022-10-12

5. A comparison between the use of machine learning techniques and the water cloud model for the retrieval of soil moisture from Sentinel-1A and Sentinel-2A products;Remote Sensing Letters;2022-08-24

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