Works matching DE "VIDEO surveillance"
Results: 2625
CROWD NAVIGATION MONITORING DURING EMERGENCIES.
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- System Research & Information Technologies / Sistemnì Doslìdžennâ ta Ìnformacìjnì Tehnologìï, 2024, n. 4, p. 43, doi. 10.20535/SRIT.2308-8893.2024.4.03
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Artificial intelligence in video surveillance systems for suspicious activity detection and incident response: A systematic literature review.
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- Advances in Science & Technology Research Journal, 2025, v. 19, n. 3, p. 389, doi. 10.12913/22998624/196795
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Panoramic Video Synopsis on Constrained Devices for Security Surveillance.
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- Systems, 2025, v. 13, n. 2, p. 110, doi. 10.3390/systems13020110
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Early Surge Warning Using a Machine Learning System with Real-Time Surveillance Camera Images.
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- Journal of Marine Science & Engineering, 2025, v. 13, n. 2, p. 193, doi. 10.3390/jmse13020193
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GeoIoU-SEA-YOLO: An Advanced Model for Detecting Unsafe Behaviors on Construction Sites.
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- Sensors (14248220), 2025, v. 25, n. 4, p. 1238, doi. 10.3390/s25041238
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Estimating little auk ( Alle alle ) breeding density and chick-feeding rate using video surveillance.
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- Polar Research, 2017, v. 36, n. 1, p. N.PAG, doi. 10.1080/17518369.2017.1374122
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Le déploiement des caméras de surveillance dans les rues et autres espaces publics au Canada : Au-delà des stratégies d'opposition et d'encadrement1.
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- Canadian Journal of Criminology & Criminal Justice, 2013, v. 55, n. 3, p. 319, doi. 10.3138/cjccj.2012-F-05
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La télésurveillance policière dans les lieux publics : l'apprentissage d'une technologie.
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- Canadian Journal of Criminology & Criminal Justice, 2010, v. 52, n. 5, p. 449, doi. 10.3138/cjccj.52.5.449
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Abnormalities detection and tracking of crowd using kinematics approach in a video stream.
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- Multimedia Tools & Applications, 2025, v. 84, n. 7, p. 3487, doi. 10.1007/s11042-024-19146-3
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Appearance and motion-based unusual crowd events detection using multiple moving objects.
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- Multimedia Tools & Applications, 2024, v. 83, n. 42, p. 90177, doi. 10.1007/s11042-024-20468-5
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Retraction Note: Real time violence detection in surveillance videos using Convolutional Neural Networks.
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- 2024
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- Correction Notice
Background subtraction for video sequence using deep neural network.
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- Multimedia Tools & Applications, 2024, v. 83, n. 35, p. 82281, doi. 10.1007/s11042-024-18843-3
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Human activity-based anomaly detection and recognition by surveillance video using kernel local component analysis with classification by deep learning techniques.
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- Multimedia Tools & Applications, 2024, v. 83, n. 35, p. 82419, doi. 10.1007/s11042-024-18711-0
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Anomaly detection in video surveillance: a supervised inception encoder approach.
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- Multimedia Tools & Applications, 2024, v. 83, n. 32, p. 78517, doi. 10.1007/s11042-024-18604-2
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Person re-identification using vision transformer and centroid triplet loss.
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- Multimedia Tools & Applications, 2024, v. 83, n. 29, p. 73777, doi. 10.1007/s11042-024-19911-4
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A deep learning-assisted visual attention mechanism for anomaly detection in videos.
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- Multimedia Tools & Applications, 2024, v. 83, n. 29, p. 73363, doi. 10.1007/s11042-023-17770-z
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Real-time video surveillance based human fall detection system using hybrid haar cascade classifier.
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- Multimedia Tools & Applications, 2024, v. 83, n. 28, p. 71599, doi. 10.1007/s11042-024-18305-w
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Twenty-five years of real-time surveillance video analytics: a bibliometric review.
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- Multimedia Tools & Applications, 2024, v. 83, n. 27, p. 69273, doi. 10.1007/s11042-024-18325-6
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TSDNN: tube sorting with deep neural networks for surveillance video synopsis.
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- Multimedia Tools & Applications, 2024, v. 83, n. 24, p. 65059, doi. 10.1007/s11042-023-18091-x
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Grid sampling based hypergraph matching technique for multiple objects tracking in video frames.
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- Multimedia Tools & Applications, 2024, v. 83, n. 22, p. 62349, doi. 10.1007/s11042-023-17486-0
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Self-trained multi-cues model for video anomaly detection.
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- Multimedia Tools & Applications, 2024, v. 83, n. 22, p. 62333, doi. 10.1007/s11042-023-16904-7
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Abnormal human activity detection by convolutional recurrent neural network using fuzzy logic.
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- Multimedia Tools & Applications, 2024, v. 83, n. 22, p. 61843, doi. 10.1007/s11042-023-15904-x
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COVID-19 monitoring system: in-browser face mask detection application using deep learning.
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- Multimedia Tools & Applications, 2024, v. 83, n. 22, p. 61943, doi. 10.1007/s11042-023-15099-1
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FRIH: A face recognition framework using image hashing.
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- Multimedia Tools & Applications, 2024, v. 83, n. 21, p. 60147, doi. 10.1007/s11042-023-18007-9
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A video codec based on background extraction and moving object detection.
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- Multimedia Tools & Applications, 2024, v. 83, n. 21, p. 59675, doi. 10.1007/s11042-023-17933-y
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A comprehensive review of datasets for detection and localization of video anomalies: a step towards data-centric artificial intelligence-based video anomaly detection.
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- Multimedia Tools & Applications, 2024, v. 83, n. 21, p. 59617, doi. 10.1007/s11042-023-17889-z
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A data stream-based approach for anomaly detection in surveillance videos.
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- Multimedia Tools & Applications, 2024, v. 83, n. 21, p. 60213, doi. 10.1007/s11042-023-17861-x
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Conjoined triple deep network for video anomaly detection.
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- Multimedia Tools & Applications, 2024, v. 83, n. 20, p. 59491, doi. 10.1007/s11042-023-17842-0
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Real-time detection of abnormal human activity using deep learning and temporal attention mechanism in video surveillance.
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- Multimedia Tools & Applications, 2024, v. 83, n. 18, p. 55981, doi. 10.1007/s11042-023-17748-x
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MP-Abr: a framework for intelligent recognition of abnormal behaviour in multi-person scenarios.
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- Multimedia Tools & Applications, 2024, v. 83, n. 18, p. 55605, doi. 10.1007/s11042-023-17667-x
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PA2Dnet based ensemble classifier for the detection of crowd anomaly detection.
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- Multimedia Tools & Applications, 2024, v. 83, n. 18, p. 53635, doi. 10.1007/s11042-023-17627-5
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Maritime traffic situation awareness analysis via high-fidelity ship imaging trajectory.
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- Multimedia Tools & Applications, 2024, v. 83, n. 16, p. 48907, doi. 10.1007/s11042-023-17456-6
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Semi-supervised anomaly detection in video surveillance by inpainting.
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- Multimedia Tools & Applications, 2024, v. 83, n. 16, p. 47677, doi. 10.1007/s11042-023-17294-6
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Appearance-motion heterogeneous networks for video anomaly detection.
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- Multimedia Tools & Applications, 2024, v. 83, n. 15, p. 44023, doi. 10.1007/s11042-023-17382-7
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A transfer learning coupled framework for distortion classification in laparoscopic videos.
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- Multimedia Tools & Applications, 2024, v. 83, n. 15, p. 45947, doi. 10.1007/s11042-023-17257-x
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An optimal intelligent video surveillance system in object detection using hybrid deep learning techniques.
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- Multimedia Tools & Applications, 2024, v. 83, n. 15, p. 44299, doi. 10.1007/s11042-023-17102-1
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FOAD: a novel video anomaly detection focusing on objects.
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- Multimedia Tools & Applications, 2024, v. 83, n. 7, p. 20637, doi. 10.1007/s11042-023-16429-z
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A deep-learning framework running on edge devices for handgun and knife detection from indoor video-surveillance cameras.
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- Multimedia Tools & Applications, 2024, v. 83, n. 7, p. 19109, doi. 10.1007/s11042-023-16231-x
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A GPU-free license plate detection based on fused color-edge and Retina approach.
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- Multimedia Tools & Applications, 2024, v. 83, n. 7, p. 18649, doi. 10.1007/s11042-023-16216-w
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Video Captioning using Sentence Vector-enabled Convolutional Framework with Short-Connected LSTM.
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- Multimedia Tools & Applications, 2024, v. 83, n. 4, p. 11187, doi. 10.1007/s11042-023-15978-7
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Concept drift adaptation in video surveillance: a systematic review.
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- Multimedia Tools & Applications, 2024, v. 83, n. 4, p. 9997, doi. 10.1007/s11042-023-15855-3
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A new person re-identification method by defining CNN-based feature extractor and sparse representation.
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- Multimedia Tools & Applications, 2024, v. 83, n. 4, p. 11043, doi. 10.1007/s11042-023-15718-x
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Joint Spatio-temporal representation based efficient video event detection using and BMCIM model.
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- Multimedia Tools & Applications, 2023, v. 82, n. 28, p. 44577, doi. 10.1007/s11042-023-15055-z
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An intelligent framework to detect and generate alert while cattle lying on road in dangerous states using surveillance videos.
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- Multimedia Tools & Applications, 2023, v. 82, n. 22, p. 34589, doi. 10.1007/s11042-023-15019-3
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A comprehensive survey on state-of-the-art video forgery detection techniques.
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- Multimedia Tools & Applications, 2023, v. 82, n. 22, p. 33499, doi. 10.1007/s11042-023-14870-8
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Fast anomaly detection in video surveillance system using robust spatiotemporal and deep learning methods.
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- Multimedia Tools & Applications, 2023, v. 82, n. 22, p. 34259, doi. 10.1007/s11042-023-14840-0
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Multi-camera BEV video-surveillance system for efficient monitoring of social distancing.
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- Multimedia Tools & Applications, 2023, v. 82, n. 22, p. 34995, doi. 10.1007/s11042-023-14416-y
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Neural networks contribution in face mask detection to reduce the spread of COVID-19.
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- Multimedia Tools & Applications, 2023, v. 82, n. 21, p. 32559, doi. 10.1007/s11042-023-14920-1
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Detection and localization of anomalies in video surveillance using novel optimization based deep convolutional neural network.
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- Multimedia Tools & Applications, 2023, v. 82, n. 19, p. 28895, doi. 10.1007/s11042-023-14917-w
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Unethical human action recognition using deep learning based hybrid model for video forensics.
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- Multimedia Tools & Applications, 2023, v. 82, n. 19, p. 28713, doi. 10.1007/s11042-023-14508-9
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