• S. Chaabouni, J. Benois-Pineau, A. Zemmari, C. Ben Amar:
      Deep saliency: prediction of interestingness in video with CNN. Visual Content Indexing and Retrieval with Psycho-Visual Models, 43-74, Springer, 2017.
    • P. Pérez de San Roman, J. Benois-Pineau, J. Domenger, F. Paclet, D. Cataert, A.  de Rugy:
      Saliency Driven Object recognition in egocentric videos with deep CNN: toward application in assistance to Neuroprostheses. Computer Vision and Image Understanding 164: 82-91 (2017)
    • S. Chaabouni, J. Benois-Pineau, F. Tison, C. Ben Amar, A. Zemmari:
      Prediction of visual attention with deep CNN on artificially degraded videos for studies of attention of patients with Dementia. Multimedia Tools Appl. 76(21): 22527-22546 (2017).
    • A. Zemmari:
      Android Malware: Will machine learning be help in hand?  (ACM SIN 2017).
    • S. Bhandari, W. Ben Jaballah, V. Jain, V. Laxmi, A. Zemmari, M. S. Gaur, M. Mosbah, M. Conti:
      Android inter-app communication threats and detection techniques. Computers & Security70: 392-421 (2017).
    • S. Chaabouni, J. Benois-Pineau, C. Ben Amar:
      Transfer learning with deep networks for saliency prediction in natural video. ICIP 2016: 1604-1608
    • P. Faruki, A. Zemmari, M. S. Gaur, V. Laxmi, M. Conti:
      MimeoDroid: Large Scale Dynamic App Analysis on Cloned Devices via Machine Learning Classifiers. DSN Workshops 2016: 60-65.
    • S. Bhandari, R. Gupta, V. Laxmi, M. S. Gaur, A. Zemmari, M. Anikeev:
      DRACO: DRoid analyst combo an android malware analysis framework. SIN 2015: 283-289.
    • O. Hamdi, M. Mbaye et F. Krief:
      A cloud-based architecture for network attack signature learning. In : New Technologies, Mobility and Security (NTMS), 2015 7th International Conference on. IEEE, 2015.
    • Amraoui, B. Benmammar, F. Krief:
      Cognitive Radio Resource Management Using Multi-Agent Systems, Auctions and Game Theory”. WSEAS Transactions on Computers 13:463-475 · January 2014