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Spatiotemporal anomaly detection using deep learning for real-time video surveillance
Rapid developments in urbanization and autonomous industrial environments have
augmented and expedited the need for intelligent real-time video surveillance. Recent …
augmented and expedited the need for intelligent real-time video surveillance. Recent …
Opportunities and Challenges of Generative Artificial Intelligence: Research, Education, Industry Engagement, and Social Impact
Generative artificial intelligence (Generative AI) is transforming the way we live and work.
Following several decades of artificial narrow intelligence, Generative AI is signaling a …
Following several decades of artificial narrow intelligence, Generative AI is signaling a …
Self-building artificial intelligence and machine learning to empower big data analytics in smart cities
The emerging information revolution makes it necessary to manage vast amounts of
unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors …
unstructured data rapidly. As the world is increasingly populated by IoT devices and sensors …
[HTML][HTML] An autonomous decision-making framework for gait recognition systems against adversarial attack using reinforcement learning
Gait identification based on Deep Learning (DL) techniques has recently emerged as
biometric technology for surveillance. We leveraged the vulnerabilities and decision-making …
biometric technology for surveillance. We leveraged the vulnerabilities and decision-making …
Self-evolving intelligent algorithms for facilitating data interoperability in IoT environments
Abstract Internet of Things (IoT) is predicted to connect 20.4 billion devices in 2020 and
surge to 75 billion by 2025. Such a connected world where machines will communicate with …
surge to 75 billion by 2025. Such a connected world where machines will communicate with …
Optimizing Generative AI Chatbots for Net-Zero Emissions Energy Internet-of-Things Infrastructure
Internet-of-Things (IoT) technologies have been steadily adopted and embedded into
energy infrastructure following the rapid transformation of energy grids through distributed …
energy infrastructure following the rapid transformation of energy grids through distributed …
Concept drift adaptation in video surveillance: A systematic review
The world we live in is dynamic by nature. Frequently, the environment changes in ways we
cannot predict. In machine learning, the phenomenon that occurs when a model has its …
cannot predict. In machine learning, the phenomenon that occurs when a model has its …
Trajectory clustering of road traffic in urban environments using incremental machine learning in combination with hyperdimensional computing
Road traffic congestion in urban environments poses an increasingly complex challenge of
detection, profiling and prediction. Although public policy promotes transport alternatives …
detection, profiling and prediction. Although public policy promotes transport alternatives …
Hierarchical two-stream growing self-organizing maps with transience for human activity recognition
The rapid growth in autonomous industrial environments has increased the need for
intelligent video surveillance. As a predominant element of video surveillance, recognition of …
intelligent video surveillance. As a predominant element of video surveillance, recognition of …
Integer self-organizing maps for digital hardware
The Self-Organizing Map algorithm has been proven and demonstrated to be a useful
paradigm for unsupervised machine learning of two-dimensional projections of …
paradigm for unsupervised machine learning of two-dimensional projections of …