Toward Explainable and Transferable Deep Downscaling of Atmospheric Pollutants-Reference-Cited by-同舟云学术

Toward Explainable and Transferable Deep Downscaling of Atmospheric Pollutants

Published:2023 Issue: Volume:20 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Ashiotis Giannis¹^ORCID,Georgiades Pantelis¹^ORCID,Christoudias Theodoros²^ORCID,Nicolaou Mihalis A.¹

Affiliation:

1. Computation-based Science and Technology Research Center (CaSToRC) - The Cyprus Institute - 2121, icosia, Cyprus

2. Climate and Atmosphere Research Centre (CAREC) - The Cyprus Institute - 2121, Nicosia, Cyprus

Funder

Cyprus Research and Innovation Foundation

Cyclone From the Cyprus Institute

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Geotechnical Engineering and Engineering Geology

Link

http://xplorestaging.ieee.org/ielx7/8859/10034981/10313233.pdf?arnumber=10313233

Reference14 articles.

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3. EfficientNet: Rethinking model scaling for convolutional neural networks;tan;arXiv 1905 11946,2019

4. High-resolution air-quality modeling in urban areas—A case study for the city of leipzig;heinold;Air Pollution Modeling and Its Application XV,2021

5. O3ResNet: A Deep Learning–Based Forecast System to Predict Local Ground-Level Daily Maximum 8-Hour Average Ozone in Rural and Suburban Environments