Composite Artificial Intelligence

1Data Fusion Techniques in Composite AI

S. Sowmyayani^1*, D. Dhanya², J. Kavitha³ and R. Roselinkiruba³

¹Department of Computer Science, St. Mary’s College (Autonomous), Thoothukudi, Tamilnadu, India

²Dept of Artificial Intelligence and Data Science, Mar Ephraem College of Engineering and Technology, Malankara Hills, Elavuvilai, Marthandam, Tamilnadu, India

³Department of CSE, VelTech Rangarajan Dr. Sagunthala, R&D Institute of Science and Technology, Chennai, Tamilnadu, India

Abstract

Nowadays, data is growing equivalent to or more than the population. At the same time, irrelevant and redundant data occupy more than the relevant ones. Considering these accounts, it is studied that data pre-processing needs special attention for any research to be more accurate. Also, it is necessary to group data according to the research. Hence, this chapter explores a few techniques that can be followed while using composite artificial intelligence (AI). A case study is elaborated to emphasize the need for data fusion and research fusion. An important and well-known Human Action Recognition (HAR) is embedded in Content-Based Video Retrieval (CBVR) to fully utilize composite AI’s efficiency. It is achieved by combining a few deep learning models to create a HAR-CBVR system and the results (features) are fused in various ways. Experiments are demonstrated with various standard datasets and the results with fusion methods are compared with a few recent methods. The results proved that the inclusion ...