Deep Learning for Geophysics: Current and Future Trends-Reference-Cited by-同舟云学术

Deep Learning for Geophysics: Current and Future Trends

Published:2021-07-15 Issue:3 Volume:59 Page:
ISSN:8755-1209
Container-title:Reviews of Geophysics
language:en
Short-container-title:Reviews of Geophysics

Author:

Yu Siwei¹,Ma Jianwei²^ORCID

Affiliation:

1. School of Mathematics Institute of Artificial Intelligence Harbin Institute of Technology Harbin China

2. School of Earth and Space Sciences Center of Artificial Intelligence Geosciences Peking University Beijing China

Funder

National Key Research and Development Program of China Stem Cell and Translational Research

National Natural Science Foundation of China

Publisher

American Geophysical Union (AGU)

Subject

Geophysics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021RG000742

Reference171 articles.

1. 3D interpolation of irregular data with a POCS algorithm

2. CWV-Net: A Deep Neural Network for Atmospheric Column Water Vapor Retrieval From Hyperspectral VNIR Data

3. $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation

4. Short‐Term Precipitation Forecast Based on the PERSIANN System and LSTM Recurrent Neural Networks

5. Application of machine learning to classification of volcanic deformation in routinely‐generated InSAR data;Anantrasirichai N.;Journal of Geophysical Research,2018

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