This paper introduces a developed multi-sensor integrated system comprising a thermal infrared camera, an RGB camera, and a LiDAR sensor, mounted on a lightweight unmanned aerial vehicle (UAV). This system is applied to the inspection tasks of levee...
Malaria is one of the major global health threats. Microscopic examination has been designated as the “gold standard” for malaria detection by the World Health Organization. However, it heavily relies on the experience of doctors, resulti...
The detection and monitoring of changes in urban buildings, as a major place for human activities, have been considered profoundly in the field of remote sensing. In recent years, comparing with other traditional methods, the deep learning-based meth...
The automation of wind turbine maintenance processes is aimed at improving the operational efficiency of wind farms through timely diagnosis of technical condition, predictive identification of potential failures, and optimization of the distribution...
Object detection in images captured by unmanned aerial vehicles (UAVs) holds great potential in various domains, including civilian applications, urban planning, and disaster response. However, it faces several challenges, such as multi-scale variati...
Flight conflict detection is fundamental to flight dispatch, trajectory planning, and flight safety control. An ever-increasing aircraft population and higher speeds, particularly the emergence of hypersonic/supersonic aircrafts, are challenging the...
Histopathology image analysis is considered as a gold standard for the early diagnosis of serious diseases such as cancer. The advancements in the field of computer-aided diagnosis (CAD) have led to the development of several algorithms for accuratel...
The stable and high-precision acquisition of attitude data is crucial for sustaining the long-term robustness of laser links to detect gravitational waves in space. We introduce an effective method that utilizes an adaptive weight optimization approa...
Community structure is one of the most important features of complex networks. Modularity-based methods for community detection typically rely on heuristic algorithms to optimize a specific community quality function. Such methods have two major limi...
Outlier detection is critical in many business applications, as it recognizes unusual behaviours to prevent losses and optimize revenue. For example, illegitimate online transactions can be detected based on its pattern with outlier detection. The pe...
Prognosis and remaining useful life (RUL) estimation of components and systems (C&S) are vital for intelligent asset-integrity management. The implementation of the traditional multi-level particle filter (TRMPF) has improved prognosis when compa...
In response to the limited accuracy of current three-dimensional (3D) object detection algorithms for small objects, this paper presents a multi-sensor 3D small object detection method based on LiDAR and a camera. Firstly, the LiDAR point cloud is pr...
In the field of road damage detection, the accuracy of existing methods still requires further improvement, particularly for elongated cracks, which are crucial for ensuring driving safety and effective road maintenance. To address this limitation, a...
In order to monitor and manage vessels in channels effectively, identification and tracking are very necessary. This work developed a maritime unmanned aerial vehicle (Mar-UAV) system equipped with a high-resolution camera and an Automatic Identifica...
The detection algorithms for water surface objects considerably assist unmanned surface vehicles in rapidly perceiving their surrounding environment, providing essential environmental information and evaluating object attributes. This study proposes...
With the rapid development of industry, people’s requirements for the functionality, stability, and safety of electronic products are becoming higher and higher. As an important medium for power supply and information transmission functions of...
To improve the detection ability of infrared small targets in complex backgrounds, an improved detection algorithm YOLO-SASE is proposed in this paper. The algorithm is based on the YOLO detection framework and SRGAN network, taking super-resolution...
Identifying spatial communities in vehicle movements is vital for sensing human mobility patterns and urban structures. Spatial community detection has been proven to be an NP-Hard problem. Heuristic algorithms were widely used for detecting spatial...
The ground is typically hidden by cloud and snow in satellite images, which have a similar visible spectrum and complex spatial distribution characteristics. The detection of cloud and snow is important for increasing image availability and studying...
Intelligent ship detection based on synthetic aperture radar (SAR) is vital in maritime situational awareness. Deep learning methods have great advantages in SAR ship detection. However, the methods do not strike a balance between lightweight and acc...
The increasing availability of diverse internet of things devices has made possible an increase in zero-day attacks, but at the same time, it has brought up several issues related to data privacy, overhead communications, and computation scalability...
With humanity entering the age of intelligence, text detection technology has been gradually applied in the industry. However, text detection in a complex background is still a challenging problem for researchers to overcome. Most of the current algo...
In complex industrial environments, accurate recognition and localization of industrial targets are crucial. This study aims to improve the precision and accuracy of object detection in industrial scenarios by effectively fusing feature information a...
Accurate identification of road objects is crucial for achieving intelligent traffic systems. However, developing efficient and accurate road object detection methods in complex traffic scenarios has always been a challenging task. The objective of t...
Extratropical cyclones (ETCs) are primary drivers of mid-latitude weather variability, yet most climatologies rely on single-level tracking, leaving their vertical structure poorly characterised. Because the vertical extent of a cyclone reflects its...
According to the survey statistics, most traffic accidents are caused by the driver’s behavior and status irregularities. Because there is no multi-level dangerous state grading system at home and abroad, this paper proposes a complex state gra...
Automatic detection of low-magnitude earthquakes has become an increasingly important research topic in recent years due to a sharp increase in induced seismicity around the globe. The detection of low-magnitude seismic events is essential for micros...
Because of the problem of low recognition accuracy in the recognition of intrusion vibration events by the distributed Sagnac type optical fiber sensing system, this paper combines the traditional optical fiber vibration signal recognition idea and t...
Remote sensing images are usually obtained from high-altitude observation. The spatial resolution of the images varies greatly and there are scale differences both between and within object classes, resulting in a diversified distribution of object s...
A key requirement in containing contagious diseases, like the COVID-19 pandemic, is the ability to efficiently carry out mass diagnosis over large populations, especially when testing resources are limited and rapid identification is essential for ou...
In large public places such as railway stations and airports, dense pedestrian detection is important for safety and security. Deep learning methods provide relatively effective solutions but still face problems such as feature extraction difficultie...
To address the limitation that existing Visual Simultaneous Localization and Mapping (VSLAM) methods fail under complex and variable illumination conditions due to the inability to extract sufficient feature points, this paper proposes a robust V SLA...
Small targets in long-distance aerial photography have the problems of small size and blurry appearance, and traditional object detection algorithms face great challenges in the field of small-object detection. With the collection of massive data in...
With an ever-increasing resolution of optical remote-sensing images, how to extract information from these images efficiently and effectively has gradually become a challenging problem. As it is prohibitively expensive to label every object in these...
The neighborhood overlap (NOVER) of an edge u-v is defined as the ratio of the number of nodes who are neighbors for both u and v to that of the number of nodes who are neighbors of at least u or v. In this paper, we hypothesize that an edge u-v with...
Automatic ship detection by Unmanned Airborne Vehicles (UAVs) and satellites is one of the fundamental challenges in maritime research due to the variable appearances of ships and complex sea backgrounds. To address this issue, in this paper, a novel...
Independent of daylight and weather conditions, synthetic aperture radar (SAR) images have been widely used for ship monitoring. The traditional methods for SAR ship detection are highly dependent on the statistical models of sea clutter or some pred...
The detection of underwater organisms represents a particularly challenging frontier within the field of computer vision. This paper proposes an underwater organism detection algorithm named the Enhanced Feature Extraction-based Underwater Organism D...
During the production process of aircraft assembly, weakly rigid parts are gradually assembled into rigid support structures in the aircraft skeleton through several assembly stations. The assembly deviations of this structure determine the quality o...
Multi-scale object detection is critical for analyzing remote sensing images. Traditional feature pyramid networks, which are aimed at accommodating objects of varying sizes through multi-level feature extraction, face significant challenges due to t...
Learning image representations with deep self-supervised models is an important task in computer vision, which aims to establish beneficial and general representations from unlabeled images. However, existing efforts train models mainly on high-level...
Computer-aided algorithm plays an important role in disease diagnosis through medical images. As one of the major cancers, lung cancer is commonly detected by computer tomography. To increase the survival rate of lung cancer patients, an early-stage...
Civil infrastructure plays a critical role in ensuring societal safety and economic development. However, structural damages such as cracks inevitably occur during long-term service. Traditional manual inspection methods are insufficient to meet the...
High-resolution optical remote sensing imagery plays a crucial role in monitoring the Earth’s surface. However, cloud obstruction and spectral confusion between clouds and snow significantly compromise data quality and application reliability,...
This study aims to develop an enhanced YOLO algorithm to improve the ship detection performance of synthetic aperture radar (SAR) in complex marine environments. Current SAR ship detection methods face numerous challenges in complex sea conditions, i...
To address the limitations of YOLOv8n in multi-scale feature representation and high false negative rates for small traffic signs under edge-computing constraints, this paper proposes an improved lightweight detection algorithm integrating the VoVGSC...
Parkinson’s disease (PD), which is a slowly progressing neurodegenerative disorder, negatively affects people’s daily lives. Early diagnosis is of great importance to minimize the effects of PD. One of the most important symptoms in the e...
Detecting surface defects on steel products is crucial for maintaining quality standards in industrial manufacturing. However, existing detection algorithms face several challenges, including the difficulty of capturing multi-scale defect characteris...
In the process of silicon single-crystal preparation, the timely identification and adjustment of abnormal conditions are crucial. Failure to promptly detect and resolve issues may result in a substandard silicon crystal product quality or even cryst...
Community detection (CD) has become an important research direction for data mining in complex networks. Evolutionary algorithm-based (EA-based) approaches, among many other existing community detection methods, are widely used. However, EA-based app...
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