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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| Fformat: | Online |
| Iaith: | Saesneg |
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MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Mynediad Ar-lein: | 27189 |
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Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
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| _version_ | 1869526377798041600 |
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| author | Hong Wei (Ed.) Feng-Bao Yang (Ed.) Shuli Sun (Ed.) Xue-Bo Jin (Ed.) |
| author_browse | Feng-Bao Yang (Ed.) Hong Wei (Ed.) Shuli Sun (Ed.) Xue-Bo Jin (Ed.) |
| author_facet | Hong Wei (Ed.) Feng-Bao Yang (Ed.) Shuli Sun (Ed.) Xue-Bo Jin (Ed.) |
| author_sort | Hong Wei (Ed.) |
| collection | Directory of Open Access Books |
| description | 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. |
| format | Online |
| id | doab-20.500.12854ir-40315 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-403152024-03-30T12:50:35Z Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 Hong Wei (Ed.) Feng-Bao Yang (Ed.) Shuli Sun (Ed.) Xue-Bo Jin (Ed.) TK1-9971 The structure and/or levels of multi-sensor fusion system Remote sensing data processing Information (speech or image Uncertain information integration Tracking from multi-sensor system The basic theory of the information fusion Knowledge cognitive based on multi-sensor system Possibility theory and other reasoning methods etc.) fusion processing Modeling by the big data from multi-sensor system Fusion decision theory thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities 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. 2021-02-11T07:49:30Z 2021-02-11T07:49:30Z 2018-06-26 15:21:03 2018 book 27189 9783038429333 9783038429340 https://directory.doabooks.org/handle/20.500.12854/40315 eng image/png Attribution-NonCommercial-NoDerivatives 4.0 International http://www.mdpi.com/books/pdfview/book/655 http://www.mdpi.com/books/pdfview/book/655 MDPI - Multidisciplinary Digital Publishing Institute 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783038429333 9783038429340 VIII, 560 open access |
| spellingShingle | TK1-9971 The structure and/or levels of multi-sensor fusion system Remote sensing data processing Information (speech or image Uncertain information integration Tracking from multi-sensor system The basic theory of the information fusion Knowledge cognitive based on multi-sensor system Possibility theory and other reasoning methods etc.) fusion processing Modeling by the big data from multi-sensor system Fusion decision theory thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities Hong Wei (Ed.) Feng-Bao Yang (Ed.) Shuli Sun (Ed.) Xue-Bo Jin (Ed.) Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 |
| title | Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 |
| title_full | Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 |
| title_fullStr | Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 |
| title_full_unstemmed | Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 |
| title_short | Advances in Multi-Sensor Information Fusion: Theory and Applications 2017 |
| title_sort | advances in multi sensor information fusion theory and applications 2017 |
| topic | TK1-9971 The structure and/or levels of multi-sensor fusion system Remote sensing data processing Information (speech or image Uncertain information integration Tracking from multi-sensor system The basic theory of the information fusion Knowledge cognitive based on multi-sensor system Possibility theory and other reasoning methods etc.) fusion processing Modeling by the big data from multi-sensor system Fusion decision theory thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities |
| topic_facet | TK1-9971 The structure and/or levels of multi-sensor fusion system Remote sensing data processing Information (speech or image Uncertain information integration Tracking from multi-sensor system The basic theory of the information fusion Knowledge cognitive based on multi-sensor system Possibility theory and other reasoning methods etc.) fusion processing Modeling by the big data from multi-sensor system Fusion decision theory thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities |
| url | 27189 |
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