On the Potential of Bayesian Neural Networks for Estimating Chlorophyll-a Concentration from Satellite Data
This work introduces the use of Bayesian Neural Networks (BNNs) for inferring chlorophyll-a concentration ([CHL-a]) from remotely sensed data. BNNs are probabilistic models that associate a probability distribution to the neural network parameters and rely on Bayes’ rule for training. The performanc...
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| Autori principali: | , , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2025-05-01
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| Serie: | Remote Sensing |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2072-4292/17/11/1826 |
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