Artificial neural networks (ANN) are a data driven tool that has been used for modeling,
prediction, optimization, classification, diagnostics, decision-making, etc., in various systems …

The remote sensing surveillance of maritime areas represents an essential task for both
security and environmental reasons. Recently, learning strategies belonging to the field of …

The size and position of a moving ship can vary greatly, resulting in different target sizes
within the image captured by an imaging device. This variability can significantly impact the …

Harsh sea conditions, uneven illumination, and the variable spatial positions of ships result
in ship images captured by imaging systems that contain not only the ship targets but also …

Maritime ship classification is essential for effectively monitoring oceanic activities but faces
challenges when using heterogeneous remote sensing data. This research presents a novel …

An operational planning procedure for a time-critical maritime unmanned aerial vehicle
(UAV) search mission is introduced and evaluated. The mission is the fast identification of a …

We research how deep learning convolutional neural networks can be used to automatically
classify the unique data set of black-and-white naval ships images from the Wright and …

Traditional sparse coding has proven to be an effective method for image feature
representation in recent years, yielding promising results in image classification. However, it …

The water body segmentation is precious for assessing its role in ecosystem services with
the circumstances of climate change and global warming. The accurate water body …

The management of small vessels has always been key to maritime administration. This
paper presents a novel method for recognizing small fishing vessels based on laser …