Underwater mines pose extreme danger for ships and submarines. Therefore, navies
around the world use mine countermeasure (MCM) units to protect against them. One of the …

Research on the automatic analysis of sonar images has focused on classical, ie non deep
learning based, approaches for a long time. Over the past 15 years, however, the application …

High-quality underwater optical images are essential for various applications of underwater
vision. However, these images often suffer from severe degradation, complex noise, low …

Underwater image restoration is of significant importance in unveiling the underwater world.
Numerous techniques and algorithms have been developed in recent decades. However …

In this paper, a new Multi-Layer Perceptron Neural Network (MLP NN) classifier is proposed
for classifying sonar targets and non-targets from the acoustic backscattered signals …

Feature selection is an effective way to reduce the data dimensionality of hyperspectral
imagery and obtain a better performance in the subsequent applications, such as …

There are many feature selection algorithms based on mutual information and three-
dimensional mutual information (TDMI) among features and the class label, since these …

To classify various sonar dataset, this paper proposes the use of the newly developed
Whale Optimization Algorithm (WOA) algorithm for training Multi-Layer Perceptrons Neural …

Abstract Multi-Layer Perceptron Neural Network (MLP NN) is one of the most applicable
tools in solving complicated problems as well as classifying between target and non-target …

Underwater automatic target recognition (ATR) is a challenging task for marine robots due to
the complex environment. The existing recognition methods basically use hand-crafted …