Camera surveillance is widely used in residential areas, highways, schools and other public places. The monitoring scanning of sudden abnormal events depend on humans. Human anomaly not only consumes a lot manpower time but also has large error detection. Video detection based AE (Auto-Encoder) currently the dominant research approach. model highly symmetrical network structure encoding decodin...

Event-based cameras are bio-inspired novel sensors that asynchronously record changes in illumination the form of events. This principle results significant advantages over conventional cameras, such as low power utilization, high dynamic range, and no motion blur. Moreover, by design, encode only relative between scene sensor not static background to yield a very sparse data structure. In this...

The problem of detecting anomalies in time series from network measurements has been widely studied and is a topic fundamental importance. Many anomaly detection methods are based on the inspection packets collected at core routers, with consequent disadvantages terms computational cost privacy. We propose an alternative method which packet header not needed. extraction normal subspace obtained...

Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly detection to the problem of identifying anomalous patterns on a subset of attributes in the data. The anomaly always depends (is conditioned) on the value of remaining attributes. The work presented in this paper focuses...

Commercial and residential buildings are responsible for a substantial portion of total global energy consumption and as a result make a significant contribution to global carbon emissions. Hence, energy-saving goals that target buildings can have a major impact in reducing environmental damage. During building operation, a significant amount of energy is wasted due to equipment and human-relat...