Detecting online abnormality in the video surveillance is a challenging issue due to streaming, video noise, outliers and resolution. Traditional trajectory based anomaly detection model which analyzes the video training patterns for anomaly detection. This paper aims to solve the problem of video noise and anomaly detection .In this paper, a novel filtered based ensemble clustering and classif...

Electroencephalography (EEG) is a useful way to implicitly monitor the user's perceptual state during multimedia consumption. One of primary challenges for practical use EEG-based monitoring achieve satisfactory level accuracy in EEG classification. Connectivity between different brain regions an important property classification EEG. However, how define connectivity structure given task still ...

The video classification task has gained significant success in the recent years. Specifically, topic more attention after emergence of deep learning models as a successful tool for automatically classifying videos. In recognition importance and to summarize this task, paper presents very comprehensive concise review on topic. There are several existing reviews survey papers related scientific ...