Using three dimensional convolutional neural networks for denoising echosounder point cloud data

Using three dimensional convolutional neural networks for denoising echosounder point cloud data

It is estimated that over 80% of the world’s oceans are unexplored and unmapped limiting our understanding of ocean systems. Due to data collection rates of modern survey technologies such as swathe multibeam echosounders (MBES) and initiatives such as Seabed 2030, there is ever-increasing increasin...

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Bibliographic Details
Main Authors: David Stephens, Andrew Smith, Thomas Redfern, Andrew Talbot, Andrew Lessnoff, Kari Dempsey
Format: Article
Language:English
Published: Elsevier 2020-03-01
Series:Applied Computing and Geosciences
Subjects:
3D convolutional neural network
Multibeam echosounder
Point cloud
Hydrographic survey
Deep learning
Bathymetry model
Online Access:http://www.sciencedirect.com/science/article/pii/S2590197419300163

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http://www.sciencedirect.com/science/article/pii/S2590197419300163

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