| Autors: Alexiev, K., Nikolova, I. N. Title: Methods for data and information fusion Keywords: data fusion; information fusion; multisensor data fusion Abstract: Correct decision making in the security sector mainly depends on information, received from multiple sources. Often, this information is insufficient, unreliable and contradictive. Multisensor data fusion systems seek to combine information from multiple sources and sensors in order to achieve inferences that cannot be achieved with a single sensor or source or in some sense better than single source information. This paper contains an analysis of the fusion theory literature in the last years. The main objective is to provide an overview of the latest state-of-the art techniques for data and information fusion and to reveal the topics, on which the scientific society efforts are nowadays concentrated. But, the outcome of this analysis would be insufficient and scanty if it concerns only the past years. That is why the authors turn on a risky deal–to forecast the future research in this field. The authors outlined the most important and interesting topics of research in the next few y References Issue
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Цитирания (Citation/s):
1. Jouirou, A., A. Baâzaoui, and W. Barhoumi. “Multi-View Information Fusion in Mammograms: A Comprehensive Overview.” Information Fusion, vol. 52, Elsevier, 2019, pp. 308–321. - 2019 - в издания, индексирани в Scopus и/или Web of Science
2. Ostromsky, T., K. Alexiev, and P. Parvanov. “Air Pollution Modelling of Accidents Involving Hazardous Substances.” Journal of Physics: Conference Series, vol. 2701, IOP Publishing, 2024, article 012021 - 2024 - в издания, индексирани в Scopus и/или Web of Science
Вид: книга/глава(и) от книга, публикация в реферирано издание