Web: http://arxiv.org/abs/2201.06616

Jan. 21, 2022, 2:11 a.m. | Mathieu Chambefort, Raphaël Butez, Emilie Chautru, Stephan Clémençon

cs.LG updates on arXiv.org arxiv.org

In image denoising problems, the increasing density of available images makes
an exhaustive visual inspection impossible and therefore automated methods
based on machine-learning must be deployed for this purpose. This is
particulary the case in seismic signal processing. Engineers/geophysicists have
to deal with millions of seismic time series. Finding the sub-surface
properties useful for the oil industry may take up to a year and is very costly
in terms of computing/human resources. In particular, the data must go through
different …

active learning arxiv data learning ml

More from arxiv.org / cs.LG updates on arXiv.org

Predictive Ecology Postdoctoral Fellow

@ Lawrence Berkeley National Lab | Berkeley, CA

Data Analyst, Patagonia Action Works

@ Patagonia | Remote

Data & Insights Strategy & Innovation General Manager

@ Chevron Services Company, a division of Chevron U.S.A Inc. | Houston, TX

Faculty members in Research areas such as Bayesian and Spatial Statistics; Data Privacy and Security; AI/ML; NLP; Image and Video Data Analysis

@ Ahmedabad University | Ahmedabad, India

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL