Tag: supervised learning

Evaluation of image features for discriminating targets from false positives in synthetic aperture sonar imagery

Abstract: With the increasing popularity of using autonomous underwater vehicles (AUVs) to gather large quantities of Synthetic Aperture Sonar (SAS) seafloor imagery, the burden on human operators to identify targets in these seafloor images has increased significantly. Existing methods of… Read More