Abstract

This paper presents a fast and accurate classification method for underwater objects using underwater mapping data obtained by a small Autonomous Underwater Vehicle (AUV) and autonomous surface vehicle (ASV). For the mapping data, in addition to underwater acoustic reflection intensity images, water depth data, point cloud data and backscattering reflection intensity data are employed. We propose the automatic classification and semantic segmentation method on deep learning using a convolutional neural network (CNN) and PointNet++. In order to verify the effectiveness of the present method, we applied it to the measured several underwater mapping data.


The PDF file did not load properly or your web browser does not support viewing PDF files. Download directly to your device: Download PDF document

Full Paper

The PDF file did not load properly or your web browser does not support viewing PDF files. Download directly to your device: Download PDF document
Back to Top
GET PDF

Document information

Published on 06/07/22
Submitted on 06/07/22

Volume 1400 Software, High Performance Computing, 2022
DOI: 10.23967/wccm-apcom.2022.087
Licence: CC BY-NC-SA license

Document Score

0

Views 9
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?