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@article{164349,
        author = {Yeshwanth Gowda LN  and Yamini Sahukar P  and B K Shrutha Keerthi  and Abhinav Shaw  and Anish Kumar},
        title = {Intelligent Surveillance System },
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {2473-2478},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164349},
        abstract = {A sophisticated intelligent surveillance system that uses advanced computer vision, machine learning, and sensor technologies to enhance security measures. The system uses deep learning techniques such as convolutional neural networks (CNNs), long short-Term memory (LSTM) networks, spatial and temporal autoencoders for object detection, tracking, enabling real-time object identification and classification. The system incorporates sensor data fusion to enhance situational awareness, detecting and responding to events in challenging conditions. The system also prioritizes privacy preservation, ensuring compliance with ethical standards and regulatory requirements. The user interface provides intuitive tools such as alerts generation, event log, anomaly highlighting for security personnel to manage and respond to potential threats. This intelligent surveillance system represents a significant advancement in security technology, offering a comprehensive and adaptable solution for enhanced surveillance, threat detection, and situational awareness in diverse environments.},
        keywords = {Intelligent Surveillance, Deep Learning, Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) Networks, Spatial and Temporal Autoencoders, Alert Generation, Event Logging, Anomaly Detection, Threat Detection.},
        month = {},
        }