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Sensors 2018, 18(4), 1162; https://doi.org/10.3390/s18041162

Advances in Multi-Sensor Information Fusion: Theory and Applications 2017

1
School of Computer Information and Engineering, Beijing Technology and Business University, Beijing 100048, China
2
School of Electronics Engineering, Heilongjiang University, Harbin 150080, China
3
Department of computer science, University of Reading, RG6 6AY Reading, UK
4
School of Information and Communication Engineering, North University of China, Taiyuan 030051, China
*
Author to whom correspondence should be addressed.
Received: 8 April 2018 / Revised: 8 April 2018 / Accepted: 9 April 2018 / Published: 11 April 2018
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Abstract

The information fusion technique can integrate a large amount of data and knowledge representing the same real-world object and obtain a consistent, accurate, and useful representation of that object. The data may be independent or redundant, and can be obtained by different sensors at the same time or at different times. A suitable combination of investigative methods can substantially increase the profit of information in comparison with that from a single sensor. Multi-sensor information fusion has been a key issue in sensor research since the 1970s, and it has been applied in many fields. For example, manufacturing and process control industries can generate a lot of data, which have real, actionable business value. The fusion of these data can greatly improve productivity through digitization. The goal of this special issue is to report innovative ideas and solutions for multi-sensor information fusion in the emerging applications era, focusing on development, adoption, and applications. View Full-Text
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Jin, X.-B.; Sun, S.; Wei, H.; Yang, F.-B. Advances in Multi-Sensor Information Fusion: Theory and Applications 2017. Sensors 2018, 18, 1162.

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