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Large model-driven hyperscale healthcare data fusion analysis in complex multi-sensors
Information FusionIn the era of big data and artificial intelligence, healthcare data fusion analysis has become difficult because of the large amounts and different types of sources involved.
Jianhui Lv +4 more
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Deep Unsupervised Blind Hyperspectral and Multispectral Data Fusion
IEEE Geoscience and Remote Sensing Letters, 2022Hyperspectral images (HSIs) usually have finer spectral resolution but coarser spatial resolution than multispectral images (MSIs). To obtain a desired HSI with higher spatial resolution, great research attention has been paid to achieving hyperspectral ...
Jiaxin Li +4 more
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Multi-Sensor Measurement and Data Fusion
IEEE Instrumentation & Measurement Magazine, 2022There is a growing demand for a reliable and comprehensive measurement of critical quantities in modern industry. As any individual sensor or measurement does not reflect the overall properties of the object, the use of multiple sensors becomes essential.
Zheng Liu +3 more
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Electronics & Communication Engineering Journal, 1997
Multisensor data fusion is a key enabling technology in which information from a number of sources is integrated to form a unified picture [1]. This concept has been applied to numerous fields and new applications are being explored constantly. Even though most multisensor data fusion applications have been developed relatively recently, the notion of ...
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Multisensor data fusion is a key enabling technology in which information from a number of sources is integrated to form a unified picture [1]. This concept has been applied to numerous fields and new applications are being explored constantly. Even though most multisensor data fusion applications have been developed relatively recently, the notion of ...
openaire +1 more source
International Journal of Remote Sensing
Numerous remote sensing (RS) systems currently collect data about Earth and its environments. However, each system provides limited data in terms of spatial resolution, spectral information, and other parameters.
F. Samadzadegan +2 more
semanticscholar +1 more source
Numerous remote sensing (RS) systems currently collect data about Earth and its environments. However, each system provides limited data in terms of spatial resolution, spectral information, and other parameters.
F. Samadzadegan +2 more
semanticscholar +1 more source
Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook
Information FusionAs cities continue to burgeon, Urban Computing emerges as a pivotal discipline for sustainable development by harnessing the power of cross-domain data fusion from diverse sources (e.g., geographical, traffic, social media, and environmental data) and ...
Xingchen Zou +10 more
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A Survey on Deep Learning for Multimodal Data Fusion
Neural Computation, 2020With the wide deployments of heterogeneous networks, huge amounts of data with characteristics of high volume, high variety, high velocity, and high veracity are generated.
Jing Gao +3 more
semanticscholar +1 more source
A Categorical Approach to Data Fusion
2006 9th International Conference on Information Fusion, 2006Using suitable topoi of presheaves, a categorical definition of measure is given. When the general definition is specialized to particular categories made of sets of possibility, probability or imprecise probability measures, the internal language of the corresponding topos gives a valid and complete proof system for the corresponding semantics.
Chemello Gaetano, Sossai Claudio
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Data fusion of multisensor data
KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516), 2002The problem of data fusion of multisensor data for multitarget tracking is considered. A hierarchical fusion system is presented for fusion of numerical data from multiple local radar stations, and a fuzzy clustering technique is introduced. Simulation results are presented for a scenario having three local radar stations and three targets with ...
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Procedings of the British Machine Vision Conference 1991, 1991
A binary classification problem is solved by acting on the combined evidence of several early vision modules. Each module gives an opinion as to the identity of an individual image element, and a consensus is reached by a trained Multi-Layer Perceptron (MLP).
David M. Booth +3 more
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A binary classification problem is solved by acting on the combined evidence of several early vision modules. Each module gives an opinion as to the identity of an individual image element, and a consensus is reached by a trained Multi-Layer Perceptron (MLP).
David M. Booth +3 more
openaire +1 more source