In autonomous driving technologies, a camera is necessary for establishing a path and detecting an object. Object recognition based on images from several cameras is required to detect impediments in autonomous ships. Furthermore, in order to avoid s...
Image recognition is vital for intelligent ships’ autonomous navigation. However, traditional methods often fail to accurately identify maritime objects’ spatial positions, especially under electromagnetic silence. We introduce the Stereo...
We developed a hybrid system combining deep learning-based recognition with fuzzy inference to enhance the detection, recognition, and identification of maritime targets. In the system, deep learning provides strong feature extraction, while fuzzy lo...
Image-based ship monitoring technology has extensive applications, and is widely used in various aspects of port management, including illegal activity surveillance, vessel identification at entry and exit points, channel and berth management, unmann...
To overcome the shortcomings of the traditional manual detection of underwater targets in side-scan sonar (SSS) images, a real-time automatic target recognition (ATR) method is proposed in this paper. This method consists of image preprocessing, samp...
Object detection is a common application within the computer vision area. Its tasks include the classic challenges of object localization and classification. As a consequence, object detection is a challenging task. Furthermore, this technique is cru...
In practice, maritime monitoring systems rely on manual work to identify the authenticities, risks, behaviours and importance of moving objects, which cannot be obtained directly through sensors, especially from marine radar. This paper proposes a ge...
The application potential of unmanned aerial vehicles (UAVs) in marine search and rescue is especially of concern for the ongoing advancement of visual recognition technology and image processing technology. Limited computing resources, insufficient...
With the continuous growth of maritime activities and the shipping trade, the application of maritime target detection in remote sensing images has become increasingly important. However, existing detection methods face numerous challenges, such as s...
The development of light detection and ranging (lidar) technology began in the 1960s, following the invention of the laser, which represents the central component of this system, integrating laser scanning with an inertial measurement unit (IMU) and...
The success of Deep Learning models, notably convolutional neural networks (CNNs), makes them the favorable solution for object recognition systems in both visible and infrared domains. However, the lack of training data in the case of maritime ships...
Cognitive workload and stress are key factors affecting human performance and safety in maritime navigation operations. This research proposes a composite gaze-tracking index, the Stress-Induced Gaze Pattern Score (SGPS), which integrates three compl...
Robust maritime radar object detection and tracking in maritime clutter environments is critical for maritime safety and security. Conventional Constant False Alarm Rate (CFAR) detectors have limited performance in processing complex-valued radar ech...
Reliable recognition of people on water from UAV imagery remains a challenging task due to strong glare, wave-induced distortions, partial submersion, and small visual scale of targets. This study proposes a hybrid method for human detection and posi...
In maritime search and rescue small object detection, existing high-accuracy detection models face deployment challenges on UAV platforms due to limited computational capabilities, while existing lightweight models often fail to meet performance requ...
SMD (Singapore Maritime Dataset) is a public dataset with annotated videos, and it is almost unique in the training of deep neural networks (DNN) for the recognition of maritime objects. However, there are noisy labels and imprecisely located boundin...
Intelligent surface vehicles, including unmanned surface vehicles (USVs) and autonomous surface vehicles (ASVs), have gained significant attention from both academic and industrial communities. However, shipboard maritime images captured under hazy w...
Background: Blockchain has been extensively discussed for enhancing transparency, traceability, and trust in general; however, there is fragmented empirical evidence available with respect to this issue within maritime logistics. The objective is to...
Recognition and understanding of ship motion patterns have excellent application value for ship navigation and maritime supervision, i.e., route planning and maritime risk assessment. This paper proposes a semantic recognition method for ship motion...
The growth of maritime transportation has been accompanied by a gradual increase in accident rates, drawing greater attention to the critical issue of man-overboard incidents and drowning. Traditional maritime search-and-rescue (SAR) methods are ofte...
Underwater acoustics has been implemented mostly in the field of sound navigation and ranging (SONAR) procedures for submarine communication, the examination of maritime assets and environment surveying, target and object recognition, and measurement...
Recently, several initiatives regarding maritime autonomous surface ships (MASSs) have been implemented worldwide. One of the fundamental technologies for attaining MASSs is the recognition and localization of surrounding ships. Traditional navigatio...
In this paper, the authors draw attention to the significant impact of the human factor during collision situations in maritime navigation. The problems in the communication process between navigators are so excessive that the authors propose automat...
This study enhances Synthetic Aperture Radar (SAR) ship detection by integrating attention mechanisms, Bi-Level Routing Attention (BRA), Swin Transformer, and a Convolutional Block Attention Module (CBAM) into state-of-the-art YOLO architectures (YOL...
Spaceborne synthetic aperture radar (SAR) represents a powerful source of data for enhancing maritime domain awareness (MDA). Wakes generated by traveling vessels hold a crucial role in MDA since they can be exploited both for ship route and velocity...
Underwater acoustic target recognition is a key enabling technology for marine environmental monitoring, resource exploration, and maritime defense. However, ship-radiated noise is strongly affected by nonstationary propagation, multipath interferenc...
Ship License Plate Recognition (SLPR) technology serves as a fundamental technological foundation for maritime transportation management. Automated ship identification enhances both regulatory oversight and operational efficiency. However, current re...
Maritime Spatial Planning (MSP) is increasingly recognized as the primary governance framework for integrating multiple and often competing maritime activities within shared marine space. This paper examines how the Multi-Use (MU) concept is incorpor...
Object recognition in remote sensing images is essential for applications such as land resource monitoring, maritime vessel detection, and emergency disaster assessment. However, detection accuracy is often limited by complex backgrounds, densely dis...
Instance segmentation accurately extracts the position and outline of ships, serving as the foundation for maritime safety tasks such as multi-object tracking, sensor fusion, and collision warning. This study focuses on single-frame segmentation and...
Object detection in single synthetic aperture radar (SAR) imagery has always been essential for SAR interpretation. Over the years, the saliency-based detection method is considered as a strategy that can overcome some inherent deficiencies in tradit...
In the field of remote sensing (RS) object detection, efficient and accurate target recognition is crucial for applications such as national defense and maritime monitoring. However, existing detection methods either have high computational complexit...
In response to the inefficiencies and high costs associated with manual buoy inspection, this paper presents the design and testing of an Autonomous Navigation Unmanned Surface Vehicle (USV) tailored for this purpose. The research is structured into...
Ship fire is one of the greatest dangers to ship navigation safety. Nevertheless, typical detection methods have limited detection effectiveness and accuracy due to distance restrictions and ship motion. Although the issue can be addressed by image r...
Fire incidents occurring onboard ships cause significant consequences that result in substantial effects. Fires on ships can have extensive and severe wide-ranging impacts on matters such as the safety of the crew, cargo, the environment, finances, r...
Synthetic Aperture Radar (SAR) is an active microwave sensor that has attracted widespread attention due to its ability to observe the ground around the clock. Research on multi-scale and multi-category target detection methods holds great significan...
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 machine learning (ML) have become a niche of interest for the communit...
In this research, E2YOLOX-VFL is proposed as a novel approach to address the challenges of optical image multi-scale ship detection and recognition in complex maritime and land backgrounds. Firstly, the typical anchor-free network YOLOX is utilized a...
With the development of the marine oil industry, leakage accidents are one of the most serious problems threatening maritime and national security. The spilt crude oil can float and sink in the water column, posing a serious long-term threat to the m...
Accurate and rapid identification of microalgae in ship ballast water is critical for preventing the spread of invasive aquatic species and ensuring ecological security. However, traditional manual microscopic examination is labor-intensive and limit...
Nowadays, engine room simulators have become an important tool for maritime training, but programming engine room simulators often involves handling large amounts of data, making the process inefficient. This paper proposes an innovative visual model...
Ship weather routing in regional seas under severe seasonal weather systems, such as typhoons, poses a critical operational challenge for maritime safety and efficiency. Traditional single-agent reinforcement learning (RL) methods frequently suffer f...