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Crop Yield Estimation and Interpretability With Gaussian Processes

  • Published:2021-12 Issue:12 Volume:18 Page:2043-2047
  • ISSN:1545-598X
  • Container-title:IEEE Geoscience and Remote Sensing Letters
  • language:
  • Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Martinez-Ferrer LauraORCID,Piles MariaORCID,Camps-Valls GustauORCID

Funder

European Research Council (ERC) through the ERC-CoG-2014 Project

Spanish Ministry of Science, Innovation and Universities (MCIU/AEI/FEDER, European Union (EU)) through the Project

Ramón y Cajal contract

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Cited by 29 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. Estimation of winter wheat yield from sentinel-1A time-series images using ensemble deep learning and a Gaussian process;Remote Sensing Letters;2024-07-31

2. Explainable Gaussian processes: a loss landscape perspective;Machine Learning: Science and Technology;2024-07-23

3. Towards Interpretable Machine Learning Metrics For Earth Observation Image Analysis;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

4. Enhancing Crop Type Classification from Multi-Frequency Dual-Pol SAR Data by Probabilistic Fusion of Gaussian Processes;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

5. Improved feature ranking fusion process with Hybrid model for crop yield prediction;Biomedical Signal Processing and Control;2024-07
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