Within the next several years, there will be a high level of autonomous technology that will
be available for widespread use, which will reduce labor costs, increase safety, save energy …

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 …

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 …

Marine debris is severely threatening the marine lives and causing sustained pollution to the
whole ecosystem. To prevent the wastes from getting into the ocean, it is helpful to clean up …

In recent years, unmanned surface vehicles (USVs) have been experiencing growth in
various applications. With the expansion of USVs' application scenes from the typical marine …

Due to the high price and heavy energy consumption of GPUs, deploying deep models on
IoT devices such as microcontrollers makes significant contributions for ecological AI …

Obstacle detection using semantic segmentation has become an established approach in
autonomous vehicles. However, existing segmentation methods, primarily developed for …

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 …

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 …

We present a survey on marine object detection based on deep neural network approaches,
which are state‐of‐the‐art approaches for the development of autonomous ship navigation …