Multisensor Data Fusion Strategies for Advanced Driver Assistance Systems

Rezaei, Mahdi; Sabzevari, Reza

doi:10.5772/6575

Cited by 9 publications

(1 citation statement)

References 14 publications

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“…Complementary information from multiple sensors allows features in the environment to be perceived that are impossible to perceive using just the information from each individual sensor operating separately [11]. Multisensor data fusion strategies are developed for advanced driver assistance systems (ADAS), see [22], where there are given data fusion concepts, an applicable model, paradigm of multisensor fusion algorithms, current sensor technologies and some applications such as object tracking, identification and classification and a providence view on next-generation car safety and driver assistance systems. The fuzzy logic approach is used in the model as sensor fusion.…”

Section: A Multisensor Data Fusionmentioning

confidence: 99%

Information Fusion in Intelligent Systems

Milovanović¹

2016

Proceedings of the International Scientific Conference - Sinteza 2016

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Abstract:Information fusion in intelligent systems is one of the basic problems. This issue is rapidly increasing since more complex systems are being developed, e.g., robotics, vision, knowledge-based systems and data mining. The process of combining several values into a single representative one is called aggregation, and we present two applications of aggregation functions in multisensor data fusion and network aggregation in sensor networks. Special attention is devoted to the situation of pairs of aggregation functions under the semiring structure (pseudo-analysis). The author shall present two applications of it in image processing.

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Section: A Multisensor Data Fusionmentioning

confidence: 99%