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	1491	Using machine learning techniques in multi-hazards assessment of Golestan National Park, Iran Enthalten in Natural hazards Bd. 117, 11.6.2023, Nr. 3, date:7.2023: 3231-3255
	1492	Using Machine Learning techniques in phenomenological studies on flavour physics Enthalten in Journal of high energy physics Bd. 2022, 19.7.2022, Nr. 7, date:7.2022: 1-43
	1493	Using Machine Learning Techniques to Detect Defects in Images of Metal Structures Enthalten in Pattern recognition and image analysis Bd. 31, 21.9.2021, Nr. 3, date:7.2021: 506-512
	1494	Using Machine Learning Techniques to Detect Parallel Patterns of Multi-threaded Applications Enthalten in International journal of parallel programming Bd. 44, 4.11.2015, Nr. 4, date:8.2016: 867-900
	1495	USING MACHINE LEARNING TECHNIQUES TO FILTER VEGETATION IN COLORIZED SFM POINT CLOUDS OF SOIL SURFACES Enthalten in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. XLVIII-1/W2-2023, 2023: 163-170. 8 S.
	1496	Using machine learning techniques to predict antimicrobial resistance in stone disease patients Enthalten in World journal of urology Bd. 40, 26.5.2022, Nr. 7, date:7.2022: 1731-1736
	1497	Using machine learning techniques to predict the cost of repairing hard failures in underground fiber optics networks Enthalten in Journal of Big Data Bd. 7, 24.8.2020, Nr. 1, date:12.2020: 1-16
	1498	Using machine learning techniques to predict the risk of osteoporosis based on nationwide chronic disease data Enthalten in Scientific reports Bd. 14, 4.3.2024, Nr. 1, date:12.2024: 1-11
	1499	Using Machine Learning Techniques to Test the Load Capacity Curve Hypothesis: A Classifier-Lasso Application on Global Panel Data Enthalten in Biophysical economics and sustainability Bd. 10, 19.2.2025, Nr. 1, date:6.2025: 1-18
	1500	Using transfer learning and dimensionality reduction techniques to improve generalisability of machine-learning predictions of mosquito ages from mid-infrared spectra Enthalten in BMC bioinformatics Bd. 24, 9.1.2023, Nr. 1, date:12.2023: 1-15

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