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Underwater threat recognition: Are automatic target classification algorithms going to replace expert human operators in the near future?
Tellez, O.L. (2019). Underwater threat recognition: Are automatic target classification algorithms going to replace expert human operators in the near future?, in: OCEANS 2019 - Marseille. pp. 4. https://hdl.handle.net/10.1109/OCEANSE.2019.8867168
In: (2019). OCEANS 2019 - Marseille. IEEE: USA. ISBN 978-1-7281-1451-4; e-ISBN 978-1-7281-1450-7. https://hdl.handle.net/10.1109/OCEANSMarseille36106.2019, more
Keyword
    Marine/Coastal
Author keywords
    mine countermeasures; synthetic aperture sonar; side-scan sonar; automatic target classification; human-in-the-loop
Author  Top 
Abstract
    In this paper, different human/machine strategies are tested in order to evaluate their performance in underwater threat recognition. Sonar images collected using synthetic aperture sonar (SAS) and side scan sonar (SSS) during real mine countermeasures exercises are used. Data are collected over a test area on the Belgian Continental Shelf, where several targets were deployed. Image resolution is divided in three categories: (1) up to 5cm pixel size, (2) between 5cm and 10cm pixel size, (3) larger than 10cm pixel size. Soil complexity is also evaluated and used to build up different strategies. Results demonstrate the utility of considering the human operator as an integral part of the automatic underwater object recognition process, as well as how automated algorithms can extend and complement human performances.
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