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Retraction: SE-stacking: Improving user purchase behavior prediction by information fusion and ensemble learning. [PDF]
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2006
Special Issue on Logic-based information fusion in artificial ...
Gregoire, Eric, Konieczny, Sébastien
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Special Issue on Logic-based information fusion in artificial ...
Gregoire, Eric, Konieczny, Sébastien
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Information fusion for information superiority
Proceedings of the IEEE 2000 National Aerospace and Electronics Conference. NAECON 2000. Engineering Tomorrow (Cat. No.00CH37093), 2002Information superiority requires the integration and exploitation of multiple data sets from a variety of sources over time and space. To collect, reduce, and enhance data, fusion can process, refine, and provide information to the correct user. This paper will discuss the importance of information fusion to information superiority through the levels ...
E. Blasch, P. Hanselman
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Information quality in information fusion
2010 13th International Conference on Information Fusion, 2010Designing fusion systems for decision support in complex dynamic situations calls for an integrated human-machine information environment, in which some processes are best executed automatically while for others the judgment and guidance of human experts and end-users are critical.
G L Rogova, E Bosse
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Information Fusion Methodology
SPIE Proceedings, 1988An approach is presented for designing multisensor electronic vision systems using information fusion concepts. A random process model of the multisensor scene environment provides a mathematical foundation for fusing information. A complexity metric is introduced to measure the level of difficulty associated with various vision tasks.
Gerald M. Flachs +2 more
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2010 13th International Conference on Information Fusion, 2010
Ensemble methods provide a principled framework for building high performance classifiers and representing many types of data. As a result, these methods can be useful for making inferences in many domains such as classification and multi-modal biometrics. We introduce a novel ensemble method for combining multiple representations (or views).
C Barbu, null Jing Peng, G Seetharaman
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Ensemble methods provide a principled framework for building high performance classifiers and representing many types of data. As a result, these methods can be useful for making inferences in many domains such as classification and multi-modal biometrics. We introduce a novel ensemble method for combining multiple representations (or views).
C Barbu, null Jing Peng, G Seetharaman
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2021
Image information fusion is an information technology and process that comprehensively processes information data from multiple image sensors to obtain more comprehensive, accurate, and reliable results than using only single sensor information data (Theodoridis and Koutroumbas 2003; Zhang 2015f).
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Image information fusion is an information technology and process that comprehensively processes information data from multiple image sensors to obtain more comprehensive, accurate, and reliable results than using only single sensor information data (Theodoridis and Koutroumbas 2003; Zhang 2015f).
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Possibility theory in information fusion
Proceedings of the Third International Conference on Information Fusion, 2000Possibility theory and the body of aggregation operations from fuzzy set theory provide some tools to address the problem of merging information coming from several sources. The approach to fusion is set-theoretic and the choice of conjunctive versus disjunctive fusion modes depends on assumptions on whether all sources are reliable or not. Quantified,
Dubois, Didier, Prade, Henri
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2018
Image fusion is a special case of information fusion, which more generally finds applications in situation analysis and decision making. If data are collected as signals quantized in pixels, an image comprises 2D pixels arranged as a picture. As shown in Fig.
Zheng Liu, Yufeng Zheng, Erik Blasch
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Image fusion is a special case of information fusion, which more generally finds applications in situation analysis and decision making. If data are collected as signals quantized in pixels, an image comprises 2D pixels arranged as a picture. As shown in Fig.
Zheng Liu, Yufeng Zheng, Erik Blasch
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