A comparative study of data input selection for deep learning-based automated sea ice mapping

Author:

Chen XinweiORCID,Cantu Fernando J. PenaORCID,Patel MuhammedORCID,Xu LinlinORCID,Brubacher Neil C.,Scott K. Andrea,Clausi David A.ORCID

Publisher

Elsevier BV

Reference34 articles.

1. Classification of sea ice types in Sentinel-1 SAR data using convolutional neural networks;Boulze;Remote Sens.,2020

2. AI4Arctic Sea Ice Challenge Dataset;Buus-Hinkler,2022

3. The influence of input variable selection on deep learning-based sea ice parameter inversion from multi-sensor satellite data;Chen,2023

4. MMSeaIce: a collection of techniques for improving sea ice mapping with a multi-task model;Chen;Cryosphere,2024

5. Weakly supervised learning for pixel-level sea ice concentration extraction using AI4Arctic sea ice challenge dataset;Chen;IEEE Geosci. Remote Sens. Lett.,2024

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