Robust Uncertainty Estimation for Classification of Maritime Objects
Jonathan Becktor,Frederik Schöller,Evangelos Boukas,Lazaros Nalpantidis,Jonathan Becktor,Frederik Schöller,Evangelos Boukas,Lazaros Nalpantidis
We explore the use of uncertainty estimation in the maritime domain, showing the efficacy on toy datasets (CIFAR10) and proving it on an in-house dataset, SHIPS. We present a method joining the intra-class uncertainty achieved using Monte Carlo Dropout, with recent discoveries in the field of outlier detection, to gain more holistic uncertainty measures. We explore the relationship between the int...
