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A Unified framework for early anomalies detection

   School of Science, Engineering and Environment

   Applications accepted all year round  Self-Funded PhD Students Only

About the Project

Civilized nations compete to provide the safest possible settings for their populations. For the sake of citizen security, most modern metropolitan areas have installed extensive networks of surveillance cameras in public parks, streets, airports, and railway-stations. 

The main goal of this PhD project is to develop a real-time solution based on cutting-edge Computer Vision and Deep Learning algorithms that can be deployed in CCTV infrastructure and monitoring grid to form a unified framework capable of detecting and identifying hazards like abnormal social behaviours, car drifting, fire etc. 

The specific goals of the PhD project are: 

  • Mathematical modelling of a light-weight and secure model for different anomalies detection.
  • Development of novel architecture and a unified frame work for detection and recognition of different anomalies for security purpose in real-time.
  • Final implementation of the unified frame work in real-time scenario with less latency.

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