Mr. James McCoy Profile

James McCoy

at Howard Univ.

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Proceedings Article | 6 June 2022 Presentation + Paper

Recent advances in multi-modal data fusion: status, challenges and perspectives

Atul Rawal, James McCoy, Adrienne Raglin, Danda Rawat, Brian Sadler

Proceedings Volume 12113, 1211318 (2022) https://doi.org/10.1117/12.2620420

KEYWORDS: Data fusion, Data modeling, Sensors, Computer security, Image encryption, Defense and security, Systems modeling, Analytical research, Head, Fuzzy logic

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Advancements in computer science, especially artificial intelligence (AI) and machine learning(ML) have brought about a scientific revolution in a plethora of military and commercial applications. One of such area has been data science, where the sheer astronomical amount of available data has spurred sub-fields of research involving its storage, analysis, and use. One such area of focus in recent years has been the fusion of data coming from multiple modalities, called multi-modal data fusion, and their use and analysis for practical and employable applications. Because of the differences within the data types, ranging from infrared/radio-frequency to audio/visual, it is extremely difficult, if not flat-out impossible, to analyze them via one singular method. The need to fuse multiple data types and sources properly and adequately for analysis, therefore arises an extra degree of freedom for data-science. This paper provides a survey for multi-modal data fusion. We provide an in-depth review of multi-modal data fusion themes, and describe the methods for designing and developing such data fusion techniques. We include an overview for the different methods and levels of data fusion techniques. An overview of security of data-fusion techniques, is also provided which highlights the present gaps within the field that need to be addressed.

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