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24 articles for “Moving Object Detection Systems”
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Traffic Detection Algorithms Analysis using ML
Abstract: It is difficult to watch traffic on crowded roads. Traffic monitoring procedures are time-consuming, expensive, labor-intensive, and require human operators. The limited accessibility hindered the storing and processing of large-scale video streams. Nonetheless, it is now possible to employe video feeds from traffic monitoring systems for number plate recognition, object tracking, traffic behavior analysis, and surveillance. Static image recognition and vehicle identification in a traffic surveillance system are very useful …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Editorial: Advancements in Movement Analysis for Understanding Neurological Disorders
Abstract: Neurological disorders pose a significant challenge, demanding innovative approaches for accurate diagnosis, effective treatment, and deeper understanding. Movement analysis emerges as a powerful tool, offering a quantitative window into the complexities of motor function. This editorial delves into the transformative impact of movement analysis on neurological research and clinical practice. Traditional diagnostic methods, reliant on subjective observations, often miss subtle motor impairments, particularly in early disease stages. Movement analysis tackles …
Published in International Journal of Brain Sciences · Vol. 1, Issue 2, 2024 · pp. 28–32 Read article
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Innovative Wireless Charging Solutions for Electric Vehicles
Abstract: As the automotive industry's future arises, electric vehicles (EVs) are at the forefront of zero-emission transportation technology. Although conventional plug-in charging stations are widely utilized, wireless power transfer (WPT) is an alternative. WPT may be used as either dynamic charging equipment for moving cars or static charging systems for parked cars. This study addresses the distinction between plug-in and wireless charging, the mechanics of wireless charging, various kinds of charging …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 11–17 Read article
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Emotion Recognition from Electroencephalogram Signal and Eye Movement Based on Deep Learning
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article