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161 - 170 von 501
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Artikel 161 Advancing soil mapping and management using geostatistics and integrated machine learning and remote sensing techniques: a synoptic review
Enthalten in Discover soil Bd. 2, 4.7.2025, Nr. 1, date:12.2025: 1-29
Online Ressource
Artikel 162 Airborne particulate matter measurement and prediction with machine learning techniques
Enthalten in Scientific reports Bd. 14, 16.8.2024, Nr. 1, date:12.2024: 1-14
Online Ressource
Artikel 163 An automated 3D modeling pipeline for constructing 3D models of MONOGENEAN HARDPART using machine learning techniques
Enthalten in BMC bioinformatics Bd. 20, 24.12.2019, Nr. 19, date:12.2019: 1-21
Online Ressource
Artikel 164 An effective correlation-based data modeling framework for automatic diabetes prediction using machine and deep learning techniques
Enthalten in BMC bioinformatics Bd. 24, 2.10.2023, Nr. 1, date:12.2023: 1-21
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Artikel 165 An efficient approach on risk factor prediction related to cardiovascular disease around Kumbakonam, Tamil Nadu, India, using unsupervised machine learning techniques
Enthalten in Scientific reports Bd. 15, 13.2.2025, Nr. 1, date:12.2025: 1-18
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Artikel 166 An innovative smart monitoring system for DED-LB/MW process stability based on machine learning techniques
Enthalten in The international journal of advanced manufacturing technology Bd. 137, 24.2.2025, Nr. 3-4, date:3.2025: 1759-1773
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Artikel 167 AN OPEN-SOURCE CANOPY CLASSIFICATION SYSTEM USING MACHINE-LEARNING TECHNIQUES WITHIN A PYTHON FRAMEWORK
Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVI-4/W2-2021, 2021: 175-182. 8 S.
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Artikel 168 Analysis of banana plant health using machine learning techniques
Enthalten in Scientific reports Bd. 14, 1.7.2024, Nr. 1, date:12.2024: 1-23
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Artikel 169 Analysis of four long non-coding RNAs for hepatocellular carcinoma screening and prognosis by the aid of machine learning techniques
Enthalten in Scientific reports Bd. 14, 28.11.2024, Nr. 1, date:12.2024: 1-12
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Artikel 170 Analysis of unsupervised and semi-supervised machine learning techniques for print defect detection during laser powder bed fusion
Enthalten in The international journal of advanced manufacturing technology Bd. 138, 27.5.2025, Nr. 9-10, date:6.2025: 4197-4212
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