In response to the safety threats posed by unauthorized unmanned aerial vehicles (UAVs), the importance of anti-UAV systems is becoming increasingly apparent. In tasks involving UAV detection, small UAVs are particularly difficult to detect due to th...
The development and implementation of a collaborative framework for aviation impact assessment studies is presented. The focus is on which technologies can be used to enable the collaborative aspect, including the use of a common data model, the secu...
Unsafe food poses a significant threat to global public health and the economy, making the early detection of food spoilage an ongoing and critical imperative. Herein, we report the design of a straightforward and highly effective fluorescence sensor...
Rapid seismic intensity estimation supports situational awareness, emergency response, and the assessment of earthquake-induced structural risk. Instrument-based systems provide authoritative measurements, but limited deployment density and installat...
There has been a great deal of research in the area of using graph engines and graph databases to model network traffic and network attacks, but the novelty of this research lies in visually or graphically representing the Reconnaissance Tactic (TA00...
Informal learning spaces (ILS) in university teaching buildings support self-directed learning, collaboration, and social interaction. However, the correspondence between configurational visual accessibility and users’ perceived accessibility r...
Image-based measurement of chopped maize stalk length remains difficult because the fragments are often slender, curved, touching, or partly overlapped. Bounding-box dimensions are therefore not reliable for length estimation, and manual measurement...
The measurement accuracy and reliability of thermography is largely limited by a relatively low spatial-resolution of infrared (IR) cameras in comparison to digital cameras. Using a high-end IR camera to achieve high spatial-resolution can be costly...
This paper presents a modular, high-fidelity simulation framework for the autonomous navigation of omnidirectional mobile robots using visual localization with AprilTags. The proposed system integrates realistic robot dynamics, a dual-layer path plan...
Mobile inspection robots require reliable license plate detection and recognition under constrained computing resources, small-scale or distant imaging conditions, motion blur, and complex background interference. To address these coupled challenges,...
Smart agriculture has become an inevitable trend in the development of modern agriculture, especially promoted by the continuous progress of large language models like chat generative pre-trained transformer (ChatGPT) and general language model (Chat...
Glaucoma is a leading cause of irreversible blindness, and timely detection and monitoring are essential to prevent permanent visual loss. Artificial intelligence (AI) has shown strong potential for automated diagnosis, but progression prediction rem...
This study developed a web-based open-source framework based on the Soil and Water Assessment Tool (SWAT), named WOF-SWAT (web-based open-source framework for SWAT), to investigate individual and combined impacts of climate change, land use change, a...
In recent decades, various assistive technologies have emerged to support visually impaired individuals. However, there remains a gap in terms of solutions that provide efficient, universal, and real-time capabilities by combining robust object detec...
Rice leaf diseases severely threaten global food security, and efficient on-site detection remains challenging for resource-constrained field inspection robots. This work introduces a lightweight visual detection framework designed for the real-time...
Camera-based visual sensing for classroom behavior detection remains challenging because fine-grained behaviors often differ only in subtle posture and hand–object cues, while dense seating, occlusion, scale variation, and background interferen...
The increasing adoption of highly glazed façades in contemporary office building has improved daylight penetration but has also intensified glare risk and sunlight overexposure in Mediterranean climates, with direct implications for occupant v...
While objective street metrics derived from imagery or GIS have become standard in urban analytics, they remain insufficient to capture subjective perceptions essential to inclusive urban design. This study introduces a novel Multimodal Street Evalua...
Due to the exponential increase in internet and social media users, fake news travels rapidly, and no one is immune to its adverse effects. Various machine learning approaches have evaluated text and images to categorize false news over time, but the...
Underwater images often suffer from luminance attenuation, structural degradation, and color distortion due to light absorption and scattering in water. The variations in illumination and color distribution across different water bodies further incre...
Artificial intelligence systems increasingly mediate high-stakes human activities, yet urban navigation remains highly challenging for blind and visually impaired individuals. Although digital navigation technologies have significantly improved route...
Autonomous Unmanned Aerial Vehicles (UAVs) have possible applications in wildlife monitoring, disaster monitoring, and emergency Search and Rescue (SAR). Autonomous capabilities such as waypoint flight modes and obstacle avoidance, as well as their a...
Accurate visual–inertial localization is essential for unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) operating in challenging environments. However, conventional multi-state constraint Kalman filter (MSCKF)-based visual&nd...
There is a massive growth in malicious software (Malware) development, which causes substantial security threats to individuals and organizations. Cybersecurity researchers makes continuous efforts to defend against these malware risks. This research...
Lung cancer, the leading cause of cancer-related mortality worldwide, necessitates better methods for earlier and more accurate detection. To this end, this study introduces LCxNet, a novel, custom-designed convolutional neural network (CNN) framewor...
Musk deer are forest-dwelling artiodactyls of high conservation value, but their wild populations remain under severe conservation pressure due to poaching driven by the demand for natural musk, together with habitat fragmentation and habitat loss. E...
The losses caused by frequent natural disasters are increasing day by day, and the short-video platform has become the core digital space for the public to pay attention to disasters and express their demands. In the face of massive multimodal data,...
Biometric authentication systems are increasingly deployed in critical security applications, yet the irreplaceable nature of biometric traits poses fundamental risks when templates are compromised. Unlike passwords or tokens, biometric data cannot b...
Sui–Tang Luoyang represents a classic achievement in Chinese capital planning, yet research remains dominated by archaeological and historical–geographical approaches, lacking a unifying theoretical framework. This research addresses this...
Paper and cellulose-based materials are known for their sensitivity to humidity, which can create stresses among fibres and increase fragility. More importantly, humidity can lead to the formation of mould and stains, compromising both aesthetic valu...
The issue of royal deaths, along with studies on the ceremonial framework, the artistic and ideological aspects of their funerals, the rituals of power succession, and the public manifestation of dynastic power, represents a significant area of resea...
This paper investigates the extent to which a mobile data source can be utilised to generate new information intelligence for decision-making in smart city planning processes. In this regard, the Mobility Explorer framework is introduced and applied...
Electroencephalogram (EEG) signals, which originate from neurons in the brain, have drawn considerable interests in identity authentication. In this paper, a face image-based rapid serial visual presentation (RSVP) paradigm for identity authenticatio...
Accurate and robust UAV navigation in complex urban environments remains challenging due to dense buildings, dynamic obstacles, and unreliable GPS signals. To address this issue, this paper proposes GLP-VO, a hybrid visual odometry framework that com...
Surgical skill assessment can quantify the quality of the surgical operation via the motion state of the surgical instrument tip (SIT), which is considered one of the effective primary means by which to improve the accuracy of surgical operation. Tra...
Covalent organic framework (COF) has been attracting considerable attention as a novel crystalline material owing to its extended π-electron conjugation and excellent spectral behavior. In this study, we present an imine-linked two-dimensional (2D...
Early pest infestations can significantly reduce chili pepper yield and quality. Therefore, timely and accurate pest detection is essential for precision pest management. However, pest detection under practical cultivation conditions remains challeng...
Maritime surveillance videos provide crucial on-spot kinematic traffic information (traffic volume, ship speeds, headings, etc.) for varied traffic participants (maritime regulation departments, ship crew, ship owners, etc.) which greatly benefits au...
This study proposes an asynchronous brain–computer interface (BCI) framework based on steady-state motion visual evoked potentials (SSMVEPs), designed to enhance the accuracy and robustness of control state recognition. The method integrates fi...
Existing visual SLAM systems with neural representations excel in static scenes but fail in dynamic environments where moving objects degrade performance. To address this, we propose a robust dynamic SLAM framework combining classic geometric feature...
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...
During the past decades, convolutional neural network (CNN)-based models have achieved notable success in remote sensing image classification due to their powerful feature representation ability. However, the lack of explainability during the decisio...
Existing single-image deraining methods often exhibit limited 2D long-range dependency modeling and underexploit frequency-domain priors. To address this, we propose SFQMamba, a dual-branch deraining network based on spatial–frequency feature f...
In recent years, the technology of artificial intelligence (AI) and robots is rapidly spreading to countries around the world. More and more scholars and industry experts have proposed AI deep learning models and methods to solve human life problems...
The transition toward Industry 4.0 requires the integration of technologically viable hardware–software–intelligence solutions into existing industrial infrastructures to enable smart and autonomous production systems. Thus, Industry 4.0...
In this study, we introduce an Unmanned Aerial Vehicle (UAV) centric visual semantic simultaneous localization and mapping (SLAM) framework that integrates RGB–D cameras, inertial measurement units (IMUs), and a 5G–enabled remote interact...
Port State Control (PSC) inspections are essential for maritime safety, but limited inspection resources make efficient vessel pre-screening increasingly important. This study investigates whether external vessel images can provide complementary info...
Urban emergency medical services (EMSs) depend on time-critical accessibility, spatial demand distribution, and resilient transport networks. This study examines how built-environment characteristics shape spatiotemporal population intensity (as a pr...
Visual Impact Assessment (VIA) is a critical tool in managing cultural heritage, evaluating the impacts of development and construction projects on the visual aspects of heritage values. However, VIA is often constrained by subjectivity, low public p...
Speech recognition approaches typically fall into three categories: audio, visual, and audio–visual. Visual speech recognition, or lip reading, is the most difficult because visual cues are ambiguous and data is scarce. To address these challen...
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