• Deep learning and low rank dictionary model for mHealth data classification 

      Said A.B.; Mohamed A.; Elfouly T.; Abualsaud K.; Harras K. ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      In the context of mobile Health (mHealth) applications, data are prone to several sources of contamination which would lead to false interpretation and misleading classification results. In this paper, a robust deep learning ...
    • Multimodal deep learning approach for Joint EEG-EMG Data compression and classification 

      Ben Said A.; Mohamed A.; Elfouly T.; Harras K.; Wang Z.J. ( Institute of Electrical and Electronics Engineers Inc. , 2017 , Conference Paper)
      In this paper, we present a joint compression and classification approach of EEG and EMG signals using a deep learning approach. Specifically, we build our system based on the deep autoencoder architecture which is designed ...
    • The inapproximability of illuminating polygons by α-floodlights 

      Abdelkader A.; Saeed A.; Harras K.; Mohamed A. ( Queen's University, Ontario, Canada , 2015 , Conference Paper)
      We consider variants of the art gallery problem where guard visibility is limited to a certain angular aperture-. We show that the problem is NP-hard even when guards can be located in the interior of the polygon. We then ...
    • UAV-based Semi-Autonomous Data Acquisition and Classification 

      Said A.B.; Mohamed A.; Elfouly T.; Abualsaud K.; Harras K. ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      In the context of mobile Health (mHealth) applications, data are prone to several sources of contamination which would lead to false interpretation and misleading classification results. In this paper, a robust deep learning ...