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Binary Time Series Classification with Bayesian Convolutional Neural Networks When Monitoring for Marine Gas Discharges
2020
Algorithms
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
doi:10.3390/a13060145
fatcat:abnb2gg2ozbdbgvj2etm4oj2xi