In maritime surveillance systems, object detection plays a crucial role in ensuring the
security of nearby waters by tracking the movement of various objects, such as ships and …

Forecasting vessel locations is of major importance in the maritime domain, with
applications in safety, logistics, etc. Nowadays, vessel tracking has become possible largely …

Compared with the classical constant false alarm ratio (CFAR) detector, the neural network
(NN)-based detector has data-driven representation learning ability, which can improve the …

High-frequency surface wave radar (HFSWR) is a powerful tool for ship detection and
surveillance. blackHowever, the use of pre-trained deep learning (DL) networks for ship …

The multilayer one-class classification (OCC) frameworks have gained great traction in
research on anomaly and outlier detection. However, most multilayer OCC algorithms suffer …

The dynamically changing ionospheric conditions are the biggest impediment to realizing
the ideal performance in long range for over-the-horizon radar (OTHR). Most related studies …

The broad learning system (BLS) is a versatile and effective tool for analyzing tabular data.
However, the rapid expansion of big data has resulted in an overwhelming amount of …

Existing salient object detection networks are large, have many parameters, are bulky and
take up a lot of computational resources. Seriously hinder its application and promotion in …

Multilayer analytic learning plays a crucial role in data mining and representation learning.
Nevertheless, most of them encounter inefficiencies in latent space encoding, resulting in …

In shipborne high-frequency surface wave radar (HFSWR), the change of platform speed or
heading will cause variations in the extension of the Doppler spectrum for vessel targets …