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

Atul Rawal; James McCoy; Adrienne Raglin; Danda B. Rawat; Brian M. Sadler

doi:10.1117/12.2620420

6 June 2022 Recent advances in multi-modal data fusion: status, challenges and perspectives

Atul Rawal, James McCoy, Adrienne Raglin, Danda B. Rawat, Brian M. Sadler

Proceedings Volume 12113, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV; 1211318 (2022) https://doi.org/10.1117/12.2620420
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

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.

Conference Presentation

Citation Download Citation

Atul Rawal, James McCoy, Adrienne Raglin, Danda B. Rawat, and Brian M. Sadler "Recent advances in multi-modal data fusion: status, challenges and perspectives", Proc. SPIE 12113, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications IV, 1211318 (6 June 2022); https://doi.org/10.1117/12.2620420

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