首页|Findings from University of Bristol in the Area of Machine Learning Described [Das-n2n: Machine Learning Distributed Acoustic Sensing (Das) Signal Denoising Without Clean Data]
Findings from University of Bristol in the Area of Machine Learning Described [Das-n2n: Machine Learning Distributed Acoustic Sensing (Das) Signal Denoising Without Clean Data]
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NETL
NSTL
Oxford Univ Press
Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Bristol, United Kingdom, by NewsRx correspondents, research stated, "This paper presents a weakly supervised machine learning method, which we call DAS-N2N, for suppressing strong random noise in distributed acoustic sensing (DAS) recordings. DAS-N2N requires no manually produced labels (i.e. pre-determined examples of clean event signals or sections of noise) for training and aims to map random noise processes to a chosen summary statistic, such as the distribution mean, median or mode, whilst retaining the true underlying signal."
BristolUnited KingdomEuropeCyborgsEmerging TechnologiesMachine LearningUniversity of Bristol
NETL
NSTL
Oxford Univ Press
