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25 articles for “Automated object recognition”
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Interview Preparation System Using AI
Abstract: The automated interview evaluation system leverages artificial intelligence (AI) and natural language processing (NLP) technologies to streamline and enhance the interview process. Through a web-based application built with the Flask framework, the system enables candidates to respond to dynamically loaded interview questions using both text and speech inputs. Questions, managed via a CSV (comma separated values) file for flexibility, are evaluated for similarity to expected answers using the rapid fuzz …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 1, 2025 · pp. 8–13 Read article
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Real-Time Object Detection and Tracking in Traffic Surveillance: Implementing Algorithms That Can Process Video Streams for Immediate Traffic Monitoring
Abstract: The rapid growth in urban development and traffic congestion calls for adopting high standards of traffic surveillance systems for monitoring. This paper reviews the current advancement and future trends of real-time object detection and tracking technology and its implications for traffic surveillance. Conventional approaches to traffic monitoring can provide more or less accurate data, but they are not easily scalable and cannot cope with rapidly changing conditions typical within urban …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 18–39 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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YOLOv8 in Focus: A Review of its Application in Driver Monitoring Systems
Abstract: This research presents a novel Driver Monitoring System (DMS) that utilises Convolutional Neural Networks (CNNs) to achieve remarkable results. Specifically, the YOLOv8 (You Only Look Once version 8) detection technique is used. The main goal is to increase road safety by using cutting-edge computer vision techniques to analyse driver behaviour in real-time. The YOLOv8 detection method, a cutting-edge CNN model renowned for its precision and effectiveness in object recognition, is …
Published in Journal of Electronic Design Technology · Vol. 14, Issue 3, 2023 · pp. 35–40 Read article
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Animal/Object Recognition and Monitoring
Abstract: This study focuses on teaching a computer to identify leopards in images through a process called Object Detection and Image Recognition. We created a special set of pictures (dataset) containing thousands of leopard images. Using a small camera module called ESP32 CAM, we trained the computer to recognize leopards by comparing the images it captures with the ones in the dataset. The results were obtained using a Convolutional Neural Network …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 1–6 Read article