The field of machine learning is witnessing its golden era as deep learning slowly becomes
the leader in this domain. Deep learning uses multiple layers to represent the abstractions of …

In the age of artificial intelligence, the best approach to handling huge amounts of data is a
tremendously motivating and hard problem. Among machine learning models, stochastic …

Real-world applications usually encounter data with various modalities, each containing
valuable information. To enhance these applications, it is essential to effectively analyze all …

With the explosion of multimedia data, semantic event detection from videos has become a
demanding and challenging topic. In addition, when the data has a skewed data distribution …

Deep learning has led to many breakthroughs in machine perception and data mining.
Although there are many substantial advances of deep learning in the applications of image …

The purpose of this study was to investigate the effectiveness of blended learning and
traditional learning on students' learning achievements and academic press. A quasi …

Numerous deep learning architectures have been designed for a variety of tasks in the past
few years. However, it is almost impossible for one model to work well for all kinds of …

In silico prediction of drug-target interaction can help to speed up the process of identifying
unknown interactions between drugs and target proteins in pharmaceutical research. In this …

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 …

In wireless data transfer, the loss of information is an important factor that reduces the power
of wireless sensor networks. In many engineering application programs, especially civil …