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Ships

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Multi-Stage Feature Extraction and Classification for Ship-Radiated Noise.

Sensors (Basel, Switzerland)
Due to the complexity and unique features of the hydroacoustic channel, ship-radiated noise (SRN) detected using a passive sonar tends mostly to distort. SRN feature extraction has been proposed to improve the detected passive sonar signal. Unfortuna...

The Application of Automatic Identification System Information and PSO-LSTM Neural Network in CRI Prediction.

Computational intelligence and neuroscience
Considering that collision accidents happen sometimes, it is necessary to predict the collision risk to ensure navigation safety. With the information construction in maritime and the popularity of automatic identification system application, it is m...

CAFC-Net: A Critical and Align Feature Constructing Network for Oriented Ship Detection in Aerial Images.

Computational intelligence and neuroscience
Ship detection is one of the fundamental tasks in computer vision. In recent years, the methods based on convolutional neural networks have made great progress. However, improvement of ship detection in aerial images is limited by large-scale variati...

Robust Ship Detection in Infrared Images through Multiscale Feature Extraction and Lightweight CNN.

Sensors (Basel, Switzerland)
The sophistication of ship detection technology in remote sensing images is insufficient, the detection results differ substantially from the practical requirements, mainly reflected in the inadequate support for the differentiated application of mul...

Path following Control of an Underactuated Catamaran for Recovery Maneuvers.

Sensors (Basel, Switzerland)
This paper focuses on the autonomous recovery maneuvers of an unknown underactuated practical catamaran, which returns to its initial position corresponding to the man overboard (MOB) by simply adjusting the rate of turn. This paper investigates the ...

Probabilistic Maritime Trajectory Prediction in Complex Scenarios Using Deep Learning.

Sensors (Basel, Switzerland)
Maritime activity is expected to increase, and therefore also the need for maritime surveillance and safety. Most ships are obligated to identify themselves with a transponder system like the Automatic Identification System (AIS) and ships that do no...

Research on the Coordinate Attention Mechanism Fuse in a YOLOv5 Deep Learning Detector for the SAR Ship Detection Task.

Sensors (Basel, Switzerland)
The real-time performance of ship detection is an important index in the marine remote sensing detection task. Due to the computing resources on the satellite being limited by the solar array size and the radiation-resistant electronic components, in...

Application of Convolutional Neural Network (CNN) to Recognize Ship Structures.

Sensors (Basel, Switzerland)
The purpose of this paper is to study the recognition of ships and their structures to improve the safety of drone operations engaged in shore-to-ship drone delivery service. This study has developed a system that can distinguish between ships and th...

A deep learning based method for intelligent detection of seafarers' mental health condition.

Scientific reports
Mental health monitoring of seafarers is an important part of achieving normal development of the ocean shipping industry. In this paper, a dual subjective-objective testing scheme is proposed to achieve a more effective and intelligent assessment of...

Short-Term Drift Prediction of Multi-Functional Buoys in Inland Rivers Based on Deep Learning.

Sensors (Basel, Switzerland)
The multi-functional buoy is an important facility for assisting the navigation of inland waterway ships. Therefore, real-time tracking of its position is an essential process to ensure the safety of ship navigation. Aiming at the problem of the low ...