Improving Satellite Imagery Masking Using Multitask and Transfer Learning

Improving Satellite Imagery Masking Using Multitask and Transfer Learning

Many remote sensing applications require masking of pixels in satellite imagery for further analysis. For instance, estimating water quality variables such as suspended sediment concentration (SSC) requires isolating pixels depicting water bodies unaffected by clouds, their shadows, terrain shadows,...

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Bibliographic Details
Main Authors: Rangel Daroya, Luisa Vieira Lucchese, Travis Simmons, Punwath Prum, Tamlin Pavelsky, John Gardner, Colin J. Gleason, Subhransu Maji
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Deep learning
global surface water detection
multitask learning
suspended sediment
transfer learning
Online Access:https://ieeexplore.ieee.org/document/10925631/
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https://ieeexplore.ieee.org/document/10925631/

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