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	991	SEN12MS – A CURATED DATASET OF GEOREFERENCED MULTI-SPECTRAL SENTINEL-1/2 IMAGERY FOR DEEP LEARNING AND DATA FUSION Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. IV-2/W7, 2019: 153-160
	992	SENTINEL-1 AND SENTINEL-2 DATA FUSION FOR WETLANDS MAPPING: BALIKDAMI, TURKEY Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLII-3, 2018: 729-734
	993	Similarity network fusion for aggregating headspace GC–MS and direct analysis in real time–mass spectrometry data from solid samples to enhance species identification efficiency of high–temperature heated wood Enthalten in Journal of wood science Bd. 68, 21.6.2022, Nr. 1, date:12.2022: 1-13
	994	Smart transportation travel model based on multiple data sources fusion for defense systems Enthalten in Soft computing Bd. 26, 7.3.2022, Nr. 7, date:4.2022: 3247-3259
	995	SOAPfuse: an algorithm for identifying fusion transcripts from paired-end RNA-Seq data In: Genome biology Bd. 14, 14.2.2013, Nr. 2, date:2.2013: 1-15
	996	Social learning for resilient data fusion against data falsification attacks Enthalten in Computational Social Networks Bd. 5, 25.10.2018, Nr. 1, date:12.2018: 1-25
	997	Soft sensor for in-line quality control of turning processes based on non-destructive testing techniques and advanced data fusion Enthalten in Production engineering Bd. 18, 20.1.2024, Nr. 2, date:4.2024: 197-206
	998	Space-time multi-level modeling for zooplankton abundance employing double data fusion and calibration Enthalten in Environmental and ecological statistics Bd. 30, 22.11.2023, Nr. 4, date:12.2023: 769-795
	999	Spatio-temporal fusion for remote sensing data: an overview and new benchmark Enthalten in Science China / Information sciences Bd. 63, 9.3.2020, Nr. 4, date:4.2020: 1-17
	1000	Spatio-Temporal Prediction of Ionospheric Total Electron Content Using an Adaptive Data Fusion Technique Enthalten in Geomagnetism and aeronomy Bd. 59, 17.3.2020, Nr. 8, date:12.2019: 971-979

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