Now showing items 1-4 of 4

    • Automated intruder detection from image sequences using minimum volume sets 

      Ahmed, Tarem; Wei, Xianglin; Ahmed, Supriyo Sabbir; Pathan, Al-Sakib Khan (© 2012 International Journal of Communication Networks and Information Security, 2012)
      We propose a new algorithm based on machine learning techniques for automatic intruder detection in visual surveillance networks. The proposed algorithm is theoretically founded on the concept of Minimum Volume Sets. Through ...
    • Efficient and effective automated surveillance agents using kernel tricks 

      Ahmed, Tarem; Pathan, Al-Sakib Khan; Ahmed, Supriyo Sabbir; Wei, Xianglin (© 2012 The Society for Modeling and Simulation International., 2012)
      Many schemes have been presented over the years to develop automated visual surveillance systems. However, these schemes typically need custom equipment, or involve significant complexity and storage requirements. In this ...
    • Learning algorithms for anomaly detection from images 

      Ahmed, Tarem; Pathan, Al Sakib Khan; Ahmed, Supriyo Shafkat (© 2017 IGI Global, 2016-08-30)
      Visual surveillance networks are installed in many sensitive places in the present world. Human security officers are required to continuously stare at large numbers of monitors simultaneously, and for lengths of time at ...
    • Taking meredith out of Grey's anatomy: automating hospital ICU emergency signaling 

      Ahmed, Tarem; Ahmed, Supriyo Shafkat; Chowdhury, Fazle Elahi (© 2016 Institute of Electrical and Electronics Engineers Inc., 2016-05)
      In this paper we propose a new algorithm based on kernel machines for automatic, instantaneous detection of emergencies occurring in a hospital Intensive Care Unit. The proposed algorithm takes as input the multitude of ...