Multi-Parameter Retrieval of Water Quality Indicators from Bayesian and Mixture Density Networks
Author:
Affiliation:
1. Science Systems and Applications Inc. (SSAI), NASA Goddard Space Flight Center,Freshwater Sensing Program,Greenbelt,MD,USA,20771
Funder
United States Geological Survey
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10281394/10281399/10281433.pdf?arnumber=10281433
Reference18 articles.
1. GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality
2. A Bayesian approach for remote sensing of chlorophyll-a and associated retrieval uncertainty in oligotrophic and mesotrophic lakes
3. Uncertainty-Aware Learning from Demonstration Using Mixture Density Networks with Sampling-Free Variance Modeling
4. Mixture density networks;bishop,1994
5. A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks
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