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	1471	Towards Model Generalization for Intrusion Detection: Unsupervised Machine Learning Techniques Enthalten in Journal of network and systems management Bd. 30, 17.10.2021, Nr. 1, date:1.2022: 1-25
	1472	TOWARDS MORE RESILIENT SMART CITIES: MT-InSAR MONITORING OF URBAN INFRASTRUCTURE USING MACHINE LEARNING TECHNIQUES Enthalten in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Bd. X-4/W3-2022, 2022: 221-228. 8 S.
	1473	Towards Waste Reduction in E-Commerce: A Comparative Analysis of Machine Learning Algorithms and Optimisation Techniques for Garment Returns Prediction with Feature Importance Evaluation Enthalten in SN Computer Science Bd. 6, 2.5.2025, Nr. 5, date:6.2025: 1-13
	1474	Type2 Diabetes Classification from Short Photoplethysmogram Signal Using Multiple Domain Features and Machine Learning Techniques Enthalten in Research on biomedical engineering Bd. 39, 22.6.2023, Nr. 3, date:9.2023: 541-560
	1475	Ultrasound-Based Ovarian Cysts Detection with Improved Machine-Learning Techniques and Stage Classification Using Enhanced Classifiers Enthalten in SN Computer Science Bd. 4, 29.7.2023, Nr. 5, date:9.2023: 1-11
	1476	Understanding live oil composition effect on asphaltene precipitation as a function of temperature change during depressurization using machine learning techniques Enthalten in Chemical papers Bd. 79, 16.11.2024, Nr. 1, date:1.2025: 353-364
	1477	Unified mRNA Subcellular Localization Predictor based on machine learning techniques Enthalten in BMC genomics Bd. 25, 7.2.2024, Nr. 1, date:12.2024: 1-18
	1478	Unmasking the sky: high-resolution PM2.5 prediction in Texas using machine learning techniques Enthalten in Journal of exposure science & environmental epidemiology Bd. 34, 1.4.2024, Nr. 5, date:9.2024: 814-820
	1479	Unraveling Magnesium Alloy Corrosion Patterns Through Unsupervised Machine Learning: Exploring Clustering Techniques for Enhanced Insight Enthalten in JOM Bd. 76, 5.6.2024, Nr. 8, date:8.2024: 4388-4403
	1480	Unraveling minds in the digital era: a review on mapping mental health disorders through machine learning techniques using online social media Enthalten in Social network analysis and mining Bd. 14, 4.4.2024, Nr. 1, date:12.2024: 1-33

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