The immense increase in multimedia-on-demand traffic that refers to audio, video, and
images, has drastically shifted the vision of the Internet of Things (IoT) from scalar to …

The ever-growing popularity of mobile devices equipped with accelerometers has provided
the opportunity to capture the semantic aspects of human activity and improve user …

In this paper, we propose a true unsupervised method to partition large-size images, where
the number of classes, training samples, and other a priori information is not known. Thus …

Affinity propagation (AP) is now among the most used methods for unsupervised
classification. However, it has two major drawbacks:(1) the number of classes (NCs) is over …

This paper proposes a semantic content analysis framework for reliable video event
detection. In this work, we target to improve the concept detection results by feeding the …

Multimedia concept detection is a challenging topic due to the well-known class imbalance
issue, where the data instances are distributed unevenly across different classes. This …

In recent years, we have witnessed a deluge of multimedia data such as texts, images, and
videos. However, the research of managing and retrieving these data efficiently is still in the …

The User Requirements Notation is a standard published by the International
Telecommunication Union that contains two complementary notations for goal and …

Learning from imbalanced data sets is a hot and challenging research topic with many real
world applications. Many studies have been conducted on integrating sampling-based …

A multimedia big data mining framework consisting of two phases for interesting event
detection in soccer videos has been proposed in this paper. In the pre-processing phase, it …