Salerno E
Ship classification SAR images Maritime surveillance
This report is concerned with the application of a Naive Bayes classification method to the identification of ship types in moderate-resolution SAR images. After a brief presentation of the principles behind the method, a simple implementation and an extensive experimentation on naive geometrical features extracted from a few thousands of targets in the OpenSARShip data set are presented. All the ship chips extracted are derived from IW GRD Sentinel 1 C-band SAR images, accompanied by AIS and MarineTraffic ground-truth data. The ideal performance of this Naive Bayes is evaluated through the standard classification indices, with respect to the ship types that are sufficiently represented in the subsets considered.
@misc{oai:it.cnr:prodotti:444831,
title = {Naive bayes for naive geometry: classifying vessels from length and beam},
author = {Salerno E},
year = {2021}
}