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Open AccessArticle

Binary Time Series Classification with Bayesian Convolutional Neural Networks When Monitoring for Marine Gas Discharges

1
Department of Mathematics, University of Bergen, 5020 Bergen, Norway
2
Department of Informatics, University of Bergen, 5020 Bergen, Norway
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Author to whom correspondence should be addressed.
Algorithms 2020, 13(6), 145; https://doi.org/10.3390/a13060145
Received: 27 February 2020 / Revised: 2 June 2020 / Accepted: 12 June 2020 / Published: 19 June 2020
The world’s oceans are under stress from climate change, acidification and other human activities, and the UN has declared 2021–2030 as the decade for marine science. To monitor the marine waters, with the purpose of detecting discharges of tracers from unknown locations, large areas will need to be covered with limited resources. To increase the detectability of marine gas seepage we propose a deep probabilistic learning algorithm, a Bayesian Convolutional Neural Network (BCNN), to classify time series of measurements. The BCNN will classify time series to belong to a leak/no-leak situation, including classification uncertainty. The latter is important for decision makers who must decide to initiate costly confirmation surveys and, hence, would like to avoid false positives. Results from a transport model are used for the learning process of the BCNN and the task is to distinguish the signal from a leak hidden within the natural variability. We show that the BCNN classifies time series arising from leaks with high accuracy and estimates its associated uncertainty. We combine the output of the BCNN model, the posterior predictive distribution, with a Bayesian decision rule showcasing how the framework can be used in practice to make optimal decisions based on a given cost function. View Full-Text
Keywords: deep learning; Bayesian convolutional neural network; uncertainty quantification; time series classification; CO2-leak detection deep learning; Bayesian convolutional neural network; uncertainty quantification; time series classification; CO2-leak detection
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Gundersen, K.; Alendal, G.; Oleynik, A.; Blaser, N. Binary Time Series Classification with Bayesian Convolutional Neural Networks When Monitoring for Marine Gas Discharges. Algorithms 2020, 13, 145.

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