International trade policy constitutes a challenging subject for undergraduate students, as it requires the integration of historical, institutional, and quantitative perspectives. This study presents a digital learning framework designed to support...
This research aims to improve dietetic-nutritional treatment using state-of-the-art RGB-D sensors and virtual reality (VR) technology. Recent studies show that adherence to treatment can be improved using multimedia technologies. However, there are f...
In this study, we propose a biologically inspired Self-Organizing Map-based Artificial Visual System (SOM-AVS) for unsupervised orientation detection in static images. By combining a biologically motivated front-end visual processing module with an u...
Medical Visual Question Answering (Med-VQA) faces significant limitations in application development due to sparse and challenging data acquisition. Existing approaches focus on multi-modal learning to equip models with medical image inference and na...
Air-to-ground visual target persistent tracking technology for swarm drones, as a crucial interdisciplinary research area integrating computer vision, autonomous systems, and swarm collaboration, has gained increasing prominence in anti-terrorism ope...
Background/Objectives: Dizziness is highly prevalent in patients with concussion, with a significant proportion of these patients experiencing visually induced dizziness (VID) in complex visual environments. As current diagnoses rely primarily on sub...
Infrared (IR) and visible (VIS) image fusion enhances vision tasks by combining complementary data. However, most existing methods assume normal lighting conditions and thus perform poorly in low-light environments, where VIS images often lose critic...
Detecting fake news is essential in natural language processing to verify news authenticity and prevent misinformation-driven social, political, and economic disruptions targeting specific groups. A major challenge in multimodal fake news detection i...
Electrical power substations are visually complex and safety-critical environments with restricted access and highly variable lighting; a digital twin (DT) framework provides a controlled and repeatable context for developing and validating vision-ba...
Visual explainable artificial intelligence (XAI) is an important mechanism for connecting analytically complex decision models with practitioners who must interpret and act upon their outputs in industrial supply chains. In facility localization prob...
Background/Objectives: Western societies introduce school-based or school-linked programs in order to improve the physical health status of students and prevent the negative impact of the late diagnosis of a series of diseases and conditions. Prescho...
Building facades are highly exposed envelope components whose degradation affects durability, habitability, urban image, and maintenance planning. Several studies address facade anomalies and service-life prediction. However, a need remains for integ...
The diagnosis of leaf diseases in medicinal and non-mainstream plants is often hindered by the scarcity of labeled samples, whereas existing deep learning methods generally rely on large-scale labeled datasets. Prototype-based few-shot methods are co...
The Internet has been progressively more integrated into daily life through its evolutionary stages, ranging from web1.0 to the current development of web3.0. These continued integrations broaden the attack surface that cybercriminals aim to exploit....
This study proposes a unified multimodal temporal motion state perception framework for optical imaging-oriented biomedical applications, integrating visual skeleton sequences, inertial measurement unit (IMU) signals, and surface electromyography (EM...
Objective and reproducible characterization of visual behavior under ecologically valid conditions remains a methodological challenge in precision sports. This pilot feasibility study presents a multimodal engineering framework that integrates progre...
In urban environments, wayfinding is a fundamental task through which individuals access essential services. Quantifying the strength of perceived cues that facilitate wayfinding can inform urban design interventions aimed at reducing potential wayfi...
Outdoor public spaces are important built-environment settings that support health, social interaction, psychological restoration, and everyday urban life. In cold-region cities, however, winter conditions such as low temperature, snow and ice, short...
Near-duplicate diagram detection in electronic documents is challenging because diagram identity depends on graphical structure, spatial composition, and textual labels, while reused images may undergo compression, cropping, rotation, photometric cha...
Understanding how seat-induced whole-body vibration (WBV) is transmitted to and actively compensated by the human body is essential for accurately assessing discomfort, fatigue, and postural control in vehicle occupants. This study proposes a visual&...
This study proposes a traceable conceptual framework for analysing and synthesising automotive product visual identity. It integrates Design for Six Sigma (DFSS) through the DMADV cycle (Define, Measure, Analyse, Design, Validate), TRIZ, and a parame...
In the context of intelligent manufacturing, deep learning-based remaining useful life (RUL) prediction has become a research hotspot in the field of Prognostics and Health Management (PHM). The traditional approaches often require strong programming...
Visual Question Answering (VQA) systems have achieved impressive performance with the rise of large-scale vision–language models (VLMs). However, these models remain vulnerable to multiple forms of multimodal bias, severely limiting their robus...
In this research, we propose a visual-feedback system and evaluate it based on motion-sensing and computational technologies. This system will help amateur athletes imitate the motor skills of professionals. Using a self-organizing map (SOM) to visua...
Ground texture-based localization leverages environment-invariant, planar-constrained features to enhance pose estimation robustness, thus offering inherent advantages for seamless localization. However, traditional feature extraction methods struggl...
This paper presents a web-based visual analytics framework for robust multi-objective aircraft wing design. Aerodynamic and structural simulation data are generated for a redesigned CRM wing, with aspect ratio and skin root thickness as key variables...
Although urban streetscape visual esthetic quality (VAQ) assessment has progressed markedly, its findings are rarely operationalized in urban planning policy-making. The resulting discontinuity in the assessment–policy linkage is a critical imp...
In the field of visual tracking, trackers based on a convolutional neural network (CNN) have had significant achievements. The fully-convolutional Siamese (SiamFC) tracker is a typical representation of these CNN trackers and has attracted much atten...
Tourist maps provide tourists with destination information that reflects their unique characteristics and cultural connotations and play an important role in attracting tourists and serving marketing purposes. However, existing designs of tourist map...
The automatic generation of language description is an important task in the intelligent analysis of aluminum alloy metallographic images, and is crucial for the high-quality development of the non-ferrous metals manufacturing industry. In this paper...
In image processing, the acquisition step plays a fundamental role because it determines image quality. The present paper focuses on the issue of blur and suggests ways of assessing contrast. The logic of this work consists in evaluating the sharpnes...
A novel fluorescent probe (C460@Tb-MOFs) was designed and synthesized by encapsulating the fluorescent dye 7-diethylamino-4-methyl coumarin (C460) into a terbium-based metal–organic framework using a simple ultrasonic impregnation method. It is...
Despite the superior performance of existing anomaly detection methods, they are often limited to single-class detection tasks, requiring separate models for each class. This constraint hinders their detection performance and deployment efficiency wh...
Intelligent sheep behavior monitoring is vital for modern husbandry, but faces severe challenges in natural pastures due to high-density flock occlusion. Traditional 2D skeleton-based networks often suffer from depth ambiguity and feature collapse, m...
The advancement of on-orbit servicing and space debris removal missions has established high-precision visual perception for non-cooperative spacecraft as a key research focus. However, the availability of high-quality, diverse spacecraft image datas...
As robots and humans start to share common spaces and perform collaborative tasks, it has become critical to facilitate information exchange between them for communicating and interpreting each other’s intentions. By overlaying virtual objects...
Real-time and drift-free state estimation is essential for the flight control of Micro Aerial Vehicles (MAVs). Due to the vibration caused by the particular flapping motion and the stringent constraints of scale, weight, and power, state estimation d...
This study presents a novel visual prompt selection framework for augmented reality (AR) applications that integrates advanced object detection and image segmentation techniques. The framework is designed to enhance user interactions and improve the...
We examine the state-of-the-art of the business analytics field by identifying and describing the four types of analytics and the three pillars of modeling. Further, we offer a framework of the interplay between the types of analytics and those pilla...
Visual sentiment analysis has become more popular than textual ones in various domains for decision-making purposes. On account of this, we develop a visual sentiment analysis system, which can classify image expression. The system classifies images...
Social media is now regarded as the most valuable source of data for trend analysis and innovative business process reengineering preferences. Data made accessible through social media can be utilized for a variety of purposes, such as by an entrepre...
This research investigates the communication barriers between designers and engineers in designing 4D Printing parts. We have proposed a conceptual design framework for 4D Printing symbols as the communication tool. Then, we have recruited sixty-fift...
In this conceptual article we propose a framework for describing the experience of delightful daylighting in Nordic homes and a method to correlate it with an existing quantitative daylighting assessment. In contrast to earlier research on daylightin...
Nowadays, with the rise of sensor technology, the amount of spatial and temporal data is increasing day by day. Modeling data in a structured way and performing effective and efficient complex queries has become more essential than ever. Online analy...
Poetic devices implicitly work towards inducing the reader to associate intended and expressed meaning to the sounds of the poem. In turn, sounds may be organized a priori into categories and assigned presumed meaning as suggested by traditional lite...
Alkaline phosphatase (ALP) is a phosphomonoester hydrolase and serves as a biomarker in various diseases. However, current detection methods for ALP rely on bulky instruments, extended time, and complex operations, which are particularly challenging...
The structural collapse of a street lighting pole represents an aspect that is often underestimated and unpredictable, but of relevant importance for the safety of people and things. These events are complex to evaluate since several sources of damag...
In addition to traditional viewing media, metadata that record the physical space from multiple perspectives will become extremely important in realizing interactive applications such as Virtual Reality (VR) and Augmented Reality (AR). This paper pro...
Recent advances in vision–language models (VLMs) have transformed the field of robotics. Researchers are combining the reasoning capabilities of large language models (LLMs) with the visual information processing capabilities of VLMs in various...
Green building rating systems (GBRS) (e.g., LEED and BREEAM) assess sustainability in the built environment but require extensive data collection and processing. In this context, digitalization strategies, such as building information Modeling (BIM),...
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