Results 201 to 210 of about 898,820 (259)
Educational anxiety and student mental health in the era of artificial intelligence: a multi-source data fusion analysis in smart education. [PDF]
Front Public HealthTian Q.
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Multimodal Data Fusion for Whole-Slide Histopathology Image Classification. [PDF]
J Healthc Inform ResSong Y +5 more
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Deep learning in multi-modal breast cancer data fusion: a literature review. [PDF]
Quant Imaging Med SurgLi T +8 more
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Retraction: Early detection and classification of Alzheimer's disease through data fusion of MRI and DTI images using the YOLOv11 neural network. [PDF]
Front NeurosciFrontiers Editorial Office.
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ACM Computing Surveys, 2009
The development of the Internet in recent years has made it possible and useful to access many different information systems anywhere in the world to obtain information. While there is much research on the integration of heterogeneous information systems, most commercial systems stop short of the actual integration of available data. Data fusion is the
Jens Bleiholder, Felix Naumann
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The development of the Internet in recent years has made it possible and useful to access many different information systems anywhere in the world to obtain information. While there is much research on the integration of heterogeneous information systems, most commercial systems stop short of the actual integration of available data. Data fusion is the
Jens Bleiholder, Felix Naumann
+4 more sources
Proceedings of the VLDB Endowment, 2011 The Web contains a significant volume of structured data in various domains, but a lot of data are dirty and erroneous, and they can be propagated through copying. While data integration techniques allow querying structured data on the Web, they take the union of the answers retrieved from different sources and can thus return conflicting information ...
Liu, X. +3 more
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The International Journal of Robotics Research, 1988
This paper treats two parts of the methodology of the fusion of multisensor data: conceptual and applied. In the concep tual part, we treat several basic questions including the fu sionability of various kinds of signals derived from the differ ent sets of raw data associated with separate sensor systems.
John M. Richardson, Kenneth A. Marsh
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This paper treats two parts of the methodology of the fusion of multisensor data: conceptual and applied. In the concep tual part, we treat several basic questions including the fu sionability of various kinds of signals derived from the differ ent sets of raw data associated with separate sensor systems.
John M. Richardson, Kenneth A. Marsh
openaire +1 more source