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Abstract Facial expressions exhibit a wide range of emotions. They are regulated by neural mechanisms in the brain that are beyond one’s control. Facial expressions are largely involuntary. The term “micro facial exp...

Abstract Wearable sensor–based human activity recognition (HAR) is central to smart sport and health-monitoring applications, yet existing deep learning models often rely on ad hoc multimodal fusion and offer limited i...

Automatic movement recognition is often used to support various fields such as clinical, sports, and security. To date, there is a lack of a classification feature that is both interpretable and not movement-specific. Pr...

ABSTRACT Analysing learners' facial expressions during learning and exploring their learning processes and emotional changes are of great significance for assisting teachers' teaching and promoting smart education. In co...

The aim of this study is the early detection of developing insulation defects in high-voltage oil-filled bushings based on the analysis of the temporal behavior of diagnostic indicators rather than only their comparison ...

Abstract Emotion recognition is fundamental to building socially intelligent robotic systems capable of effective and adaptive Human-Robot Interaction (HRI) and Collaboration (HRC). This literature review synthesizes rec...

Dynamic gesture recognition is a core technology for human–computer interaction, yet existing methods face prominent limitations in hand spatial topology modeling, long–short-term temporal feature fusion, and general...

Face-recognition technology is one of the most important advancements in the field of computer vision. They play a crucial role in many applications, including biometric authentication, surveillance, online security, and...

Abstract Facial Expression Recognition (FER) demonstrates significant value in practical scenarios such as intelligent human–computer interaction. However, conventional FER methods often struggle to balance performance...

Abstract GIS (Gas-insulated switchgear) is a critical component of modern power grids, and accurate awareness of its internal insulation condition is essential to power system safety. PD (Partial Discharge) is a key indi...

Abstract With the development of sports rehabilitation, accurate assessment of the patient’s rehabilitation process has become the key to enhance the rehabilitation effect. To solve the problems of inaccurate recogniti...

Anions are ionic species that play important roles in biology, medicine, catalysis, and environmental science. Identifying these species is crucial for industrial applications and clinical diagnostics. In recent years, e...

Background For those with hearing loss, sign language (SL) is an essential communication tool. The most common and basic type of SL is American SL (ASL). ASL plays a vital role in various communicative contexts, includin...

Abstract To improve sketch recognition accuracy, this study proposes an enhanced sketch recognition model based on an improved CycleGAN network and a dual attention mechanism. The proposed model first incorporates multi-...

The perception systems for Traffic Sign Recognition (TSR) and Lane Line Recognition (LLR) are foundational pillars for the safe and effective operation of Advanced Driver-Assistance Systems (ADAS) and fully autonomous ve...

Emotion recognition is a relevant capability for understanding human behavior, enabling interactive systems to support natural interaction with their users. Among the diverse ways the literature tackles this task, gait e...

Currently, much effort is devoted to improving the accuracy of Wi-Fi sensing. Despite the typically high density of modern Wi-Fi deployments, in many scenarios, the number of access points under control is limited, which...

The investigation aims to address the pressing issue of excessive administrative burden on medical personnel in Ukraine, which leads to significant time expenditures and the risk of errors in manual documentation. As a r...

Net One of the biggest challenges in industrial robotics working in dynamic environments is reliably recognizing voice commands for human-robot interaction. This article presents a Hybrid Hidden Markov Model, Convolution...

Abstract Recognizing tactical formations is a critical task in professional football performance analytics. However, existing methods often fail to capture the dynamic and continuously evolving nature of modern tactical ...

Inborn errors of immunity (IEI) are increasing in number, and prompt recognition and diagnosis remain a challenge for clinicians. Use of machine learning (ML) for clinical pattern recognition is promising but has been li...

IntroductionUnderstanding how children recognize facial emotions is essential for explaining the development of social communication. During the COVID-19 pandemic, widespread mask-wearing partially occluded facial expres...

The key component of contemporary biometric security systems is the accurate identification and validation of individuals using facial recognition technology. Advanced security systems can now be personalized through imp...

Abstract DriveEmo-FL presents a privacy-preserving, radar-based emotion-recognition framework tailored for autonomous-vehicle (AV) cabins. Leveraging a compact embedded mmWave radar, the system captures upper-body emotio...