Bayesian Neural Networks to Analyze Hyperspectral Datasets Using Uncertainty Metrics

Author:

Alcolea Adrian1ORCID,Resano Javier1ORCID

Affiliation:

1. Group of Computer Architecture (GaZ), Engineering Research Institute of Aragon (I3A), University of Zaragoza, Zaragoza, Spain

Funder

Agencia Estatal de Investigación

European Regional Development Fund

Research Group from Department of Science, University and Knowledge Society, Government of Aragón

Government of Aragón through the European Social Fund “Construyendo Europa desde Aragón” of the European Union

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Reference28 articles.

1. Active Learning With Convolutional Neural Networks for Hyperspectral Image Classification Using a New Bayesian Approach

2. Bayesian convolutional neural networks with Bernoulli approximate variational inference;gal;arXiv 1506 02158,2015

3. Retrieval of Water Quality Parameters from Hyperspectral Images Using Hybrid Bayesian Probabilistic Neural Network

4. Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty

5. On calibration of modern neural networks;guo;Proc 34th Int Conf Mach Learn (ICML),2017

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