Ship Detection in SAR Images Using Convolutional Variational Autoencoders
N. M. Fonseca Ferreira, Margarida Silveira · 2020
We propose an unsupervised framework for ship detection in SAR image data, based on anomaly detection. We first learn representations of the SAR images with a convolutional Variational Autoencoder. Aftwerwards, we perform anomaly detection based on those representations, with a clustering algorithm. Experimental results with real SAR data are provided to illustrate the performance of the proposed algorithm.