Browsing by Subject "Anomaly Detection"

Now showing items 1-6 of 6

    • 3D point cloud enhancement using unsupervised anomaly detection 

      Regaya, Yousra; Fadli, Fodil; Amira, Abbes ( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2019 , Conference Paper)
      3D point cloud is increasingly getting attention for perceiving 3D environment which is needed in many emerging applications. This data structure is challenging due to its characteristics and the limitation of the acquisition ...

    • Battery-Induced Load Hiding and Its Utility Consequences 

      Aly, Hussein; Altamimi, Emran; Al-Ali, Abdulaziz; Al-Ali, Abdulla; Malluhi, Qutaibah ( Institute of Electrical and Electronics Engineers Inc. , 2024 , Conference Paper)
      The introduction of smart grids allows utility providers to collect detailed data about consumers, which can be utilized to enhance grid efficiency and reliability. However, this data collection also raises privacy concerns. ...

    • Detecting market manipulation in stock market data 

      Al-Thani, Haya A (2017 , Master Thesis)
      Anomaly Detection is an extensively researched problem that has diverse applications in many domains. Anomaly detection is the process of finding data points or patterns that do not conform to expected behavior within a ...

    • TOWARDS A SAFER METAVERSE: ANOMALY DETECTION IN AVATAR ACTIONS USING HUMAN ACTION TRANSFER LEARNING 

      ELTANBOULY, SOMAYA SALAH (2024 , Master Thesis)
      The Metaverse has captured global attention as a potential frontier for the internet's future. Avatar actions within this immersive digital realm mirror real-world behaviors, introducing safety concerns like cyberbullying ...

    • A Two-Stage Energy Anomaly Detection for Edge-based Building Internet of Things (BIoT) Applications 

      Himeur, Yassine; Fadli, Fodil; Amira, Abbes ( Institute of Electrical and Electronics Engineers Inc. (IEEE) , 2022 , Conference Paper)
      The Building Internet of Energy (BIoE) is quite promising for curtailing energy consumption, reducing costs, and promoting building transformation. Integrating Artificial Intelligence into the BIoE is essential for big ...

    • Unsupervised Technique for Anomaly Detection in Qatar Stock Market 

      Al-Thani H.; Hassen H.; Al-Maadced S.; Fetais N.; Jaoua A. ( Institute of Electrical and Electronics Engineers Inc. , 2018 , Conference Paper)
      The aim of anomaly detection is to find patterns or data points that are not confirming the expected behavior inside the dataset. Techniques from a variety of disciplines like machine learning, statistics, information ...