Deep Learning for Precipitation Retrievals Using ABI and GLM Measurements on the GOES-R Series-Reference-Cited by-同舟云学术

Deep Learning for Precipitation Retrievals Using ABI and GLM Measurements on the GOES-R Series

Author:

Yang Yifan¹^ORCID,Chen Haonan¹^ORCID,Hilburn Kyle A.²,Kuligowski Robert J.³^ORCID,Cifelli Robert⁴

Affiliation:

1. Department of Electrical and Computer Engineering, Colorado State University, Fort Collins, CO, USA

2. Cooperative Institute for Research in the Atmosphere (CIRA), Colorado State University, Fort Collins, CO, USA

3. National Oceanic and Atmospheric Administration (NOAA)/NESDIS Center for Satellite Applications and Research (STAR), College Park, MD, USA

4. National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Laboratory, Boulder, CO, USA

Funder

National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS) Proving Ground and Risk Reduction (PGRR) Program

National Science Foundation (NSF) CAREER Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

Reference40 articles.

4. An intriguing failing of convolutional neural networks and the coordconv solution;liu;Proc Adv Neural Inf Process Syst,2018

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