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Multi-Sensor Measurement and Data Fusion
IEEE Instrumentation & Measurement Magazine, 2022Zheng Liu 0002 +3 more
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Multi-Sensor Data Fusion (MSDF)
2017The Data Fusion Model maintained by the JDL (Joint Directors of Laboratories) Data Fusion Group is the most widely-used method for categorizing data fusion-related functions. This paper discusses the current effort to revise and expand this model to facilitate the cost-effective development, acquisition, integration and operation of multi-sensor/multi ...
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Multi Sensor Data Fusion With Risk Assessment
2019 International Conference on Advanced Electrical Engineering (ICAEE), 2019In robotic field, autonomous navigation safely is a timely subject. Therefore, many researchers try to elaborate a reliable system to respond this exigency. Among these systems, we mention multi sensor data fusion. The data fusion is an active field of research, It is almost applied in all domains. it is resolved by several manner. The best represented
Elhaouari Kobzili +5 more
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Multi-sensor data fusion in defence and aerospace
The Aeronautical Journal, 1998AbstractThe UK OST Technology Foresight for defence and aerospace identified multi-sensor data fusion as a future critical enabling technology for the UK, requiring a coordinated research agenda. This review paper provides an overview of past research and applications of data fusion.
Harris, C.J., Bailey, A., Dodd, T.J.
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Clustering Methods for Multi-sensor Data Fusion
2012 International Conference on Industrial Control and Electronics Engineering, 2012In the network-centric warfare, the complete battlefield situation information and attack information for weapons can be collected and calculated by multiple sensor platforms, and the results can be distributed to the command and control systems and weapon platforms to complete target attack tasks.
Liu Han, Zhang Lei
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Context-Awareness for Multi-sensor Data Fusion in Smart Environments
2016Multi-sensor data fusion is extensively used to merge data collected by heterogeneous sensors deployed in smart environments. However, data coming from sensors are often noisy and inaccurate, and thus probabilistic techniques, such as Dynamic Bayesian Networks, are often adopted to explicitly model the noise and uncertainty of data.
DE PAOLA, Alessandra +3 more
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Sensor Modeling and Multi-Sensor Data Fusion
2005Abstract : This research report presents a novel strategy to develop a sensor model based on a probabilistic approach that would accurately provide information about individual sensor's uncertainties and limitations. The strategy also establishes the dependence of sensor's uncertainties on some of environmental parameters or parameters of any feature ...
Manish Kumar, Devendra P. Garg
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Multi-temporal Multi-sensor Data Fusion
2014Landsat data offered a great help in mapping a lot of vegetation parameters at 30 m spatial resolution but unfortunately does not provide daily coverage (it has a 16 day revisit cycle). This is a major obstacle for monitoring short term disturbances and changes in vegetation characteristics through time.
Ghannam, Sherin, Abbott, A. Lynn
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Non-contact diagnosis for gearbox based on the fusion of multi-sensor heterogeneous data
Information Fusion, 2023Ke Feng, Yongbo Li
exaly
Multi-sensor fusion for body sensor network in medical human–robot interaction scenario
Information Fusion, 2020Kai Lin, Dongsheng Zhou, Qiang Zhang
exaly