Accuracy, Efficiency, and Transferability of a Deep Learning Model for Mapping Retrogressive Thaw Slumps across the Canadian Arctic

Accuracy, Efficiency, and Transferability of a Deep Learning Model for Mapping Retrogressive Thaw Slumps across the Canadian Arctic

Deep learning has been used for mapping retrogressive thaw slumps and other periglacial landforms but its application is still limited to local study areas. To understand the accuracy, efficiency, and transferability of a deep learning model (i.e., DeepLabv3+) when applied to large areas or multiple...

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Bibliographic Details
Main Authors: Lingcao Huang, Trevor C. Lantz, Robert H. Fraser, Kristy F. Tiampo, Michael J. Willis, Kevin Schaefer
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Remote Sensing
Subjects:
DeepLab
domain adaptation
generative adversarial network
permafrost
thermokarst
Online Access:https://www.mdpi.com/2072-4292/14/12/2747

Internet

https://www.mdpi.com/2072-4292/14/12/2747

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