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Res: A lightweight Deep Learning model for Quantitative Precipitation Nowcasting Based on New Transformer Customized for Remote Sensing Data

Authors: Li, Dawei;

Res: A lightweight Deep Learning model for Quantitative Precipitation Nowcasting Based on New Transformer Customized for Remote Sensing Data

Abstract

This is the source code of Res, which is a new transformer model we designed for QPN tasks. The manuscript is currently under review, and we do not upload a preprint version, so it is partially accessible. You can apply for it if meet the following conditions. Once our manuscript be accepted, we will make it open source and upload another version. If you are interested in our work, please stay tuned for this repository.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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OpenAIRE UsageCountsViews provided by UsageCounts
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