Underwater image processing is an intelligence research field that has great potential to
help developers better explore the underwater environment. Underwater image processing …

Efficient convolutional neural networks (CNNs) are designed and trained for an underwater
target classification task with synthetic aperture sonar (SAS) imagery collected at sea. The …

Image dehazing play a vital role in several applications related to computer vision. The
prime motive of this paper is to provide the overview of the existing deep learning algorithms …

Among underwater perceptual sensors, imaging sonar has been highlighted for its
perceptual robustness underwater. The major challenge of imaging sonar, however, arises …

Sonar is widely used in marine water cleaning tasks, so sonar images have become an
effective tool for garbage detection and underwater scene analysis. However, it is an …

A new algorithm called the Mondrian detector has been developed for object detection in
high-frequency synthetic aperture sonar (SAS) imagery. If a second (low) frequency-band …

Pooling layers (eg max and average) may overlook important information encoded in the
spatial arrangement of pixel intensity and/or feature values. We propose a novel lacunarity …

Underwater crime scene investigation and emergency response are tasks typically carried
out by divers constituting part of a specialist team. Operating in such dynamic environments …

Deep learning has enabled significant improvements in semantic image segmentation,
especially in underwater imaging domains such as side scan sonar (SSS). In this work, we …

This paper proposes a method to perform on-line multi-class segmentation of Side-Scan
Sonar acoustic images, thus being able to build a semantic map of the sea bottom usable to …