Aljaloud, Abdulaziz Salamah; Ullah, Habib (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-05-17)
Analyzing unusual events is significantly important for video surveillance to ensure people
safety. These events are characterized by irregular patterns that do not conform to the expected behavior
in the surveillance scenes. We present a novel irregularity-aware semi-supervised deep learning model
(IA-SSLM) for detection of unusual events. While most existing works depend on the availability ...