Browsing AURA by Author "Sharif, Md Haidar"

Now showing items 1-3 of 3

    • CNN-ViT Supported Weakly-Supervised Video Segment Level Anomaly Detection 

      Sharif, Md Haidar; Lei, Jiao; Omlin, Christian Walter Peter (Peer reviewed; Journal article, 2023)
      Video anomaly event detection (VAED) is one of the key technologies in computer vision for smart surveillance systems. With the advent of deep learning, contemporary advances in VAED have achieved substantial success. ...

    • Deep Crowd Anomaly Detection by Fusing Reconstruction and Prediction Networks 

      Sharif, Md Haidar; Lei, Jiao; Omlin, Christian Walter Peter (Peer reviewed; Journal article, 2023)
      Abnormal event detection is one of the most challenging tasks in computer vision. Many existing deep anomaly detection models are based on reconstruction errors, where the training phase is performed using only videos of ...

    • ERCP: Energy-Efficient and Reliable-Aware Clustering Protocol for Wireless Sensor Networks 

      El-Fouly, Fatma H.; Khedr, Ahmed Y.; Sharif, Md Haidar; Alreshidi, Eissa Jaber; Yadav, Kusum; Kusetogullari, Huseyin; Ramadan, Rabie A. (Peer reviewed; Journal article, 2022)
      Wireless Sensor Networks (WSNs) have been around for over a decade and have been used in many important applications. Energy and reliability are two of the major problems with these kinds of applications. Reliable data ...