Autonomous ships are expected to improve the level of safety and efficiency in future
maritime navigation. Such vessels need perception for two purposes: to perform …

Due to the rapid development of deep learning techniques, numerous frameworks including
convolutional neural networks (CNNs), deep belief networks (DBNs) and auto-encoder (AE) …

SMD (Singapore Maritime Dataset) is a public dataset with annotated videos, and it is almost
unique in the training of deep neural networks (DNN) for the recognition of maritime objects …

Abstract We introduce Meta-Album, an image classification meta-dataset designed to
facilitate few-shot learning, transfer learning, meta-learning, among other tasks. It includes …

Small-sized unmanned surface vehicles (USV) are coastal water devices with a broad range
of applications such as environmental control and surveillance. A crucial capability for …

The primary task of marine surveillance is to construct a perfect marine situational
awareness (MSA) system that serves to safeguard national maritime rights and interests and …

Object detection in maritime environments is a rather unpopular topic in the field of computer
vision. In contrast to object detection for automotive applications, no sufficiently …

The volume of data generated by today's digitally connected world is enormous, and a
significant portion of it is publicly available. These data sources are web archives, public …

Deep learning-based visual perception of an unmanned surface vehicle (USV) essentially
benefits from informative images. It is unfortunately short of available datasets of marine …

In the last five years, the state-of-the-art in computer vision has improved greatly thanks to an
increased use of deep convolutional neural networks (CNNs), advances in graphical …