Advances in Multi-Sensor Information Fusion: Theory and Applications 2017
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...
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Format: | Electronic Book Chapter |
Language: | English |
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MDPI - Multidisciplinary Digital Publishing Institute
2018
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Online Access: | DOAB: download the publication DOAB: description of the publication |
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100 | 1 | |a Hong Wei (Ed.) |4 auth | |
700 | 1 | |a Feng-Bao Yang (Ed.) |4 auth | |
700 | 1 | |a Shuli Sun (Ed.) |4 auth | |
700 | 1 | |a Xue-Bo Jin (Ed.) |4 auth | |
245 | 1 | 0 | |a Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 |
260 | |b MDPI - Multidisciplinary Digital Publishing Institute |c 2018 | ||
300 | |a 1 electronic resource (VIII, 560 p.) | ||
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520 | |a 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, such as geospatial information systems, business intelligence, oceanography, discovery science, intelligent transport systems, wireless sensor networks, etc. Recently, thanks to the vast development in sensor and computer memory technologies, more and more sensors are being used in practical systems and a large amount of measurement data are recorded and restored, which may actually be the "time series big data". For example, sensors in machines 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 on innovative ideas and solutions for the methods of multi-sensor information fusion in the emerging applications era, focusing on development, adoption and applications. | ||
540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
546 | |a English | ||
650 | 7 | |a Energy industries & utilities |2 bicssc | |
653 | |a The structure and/or levels of multi-sensor fusion system | ||
653 | |a Remote sensing data processing | ||
653 | |a Information (speech or image | ||
653 | |a Uncertain information integration | ||
653 | |a Tracking from multi-sensor system | ||
653 | |a The basic theory of the information fusion | ||
653 | |a Knowledge cognitive based on multi-sensor system | ||
653 | |a Possibility theory and other reasoning methods | ||
653 | |a etc.) fusion processing | ||
653 | |a Modeling by the big data from multi-sensor system | ||
653 | |a Fusion decision theory | ||
856 | 4 | 0 | |a www.oapen.org |u http://www.mdpi.com/books/pdfview/book/655 |7 0 |z DOAB: download the publication |
856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/40315 |7 0 |z DOAB: description of the publication |