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Ergebnis der Suche nach: "Machine Learning"
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Artikel 421 Quality control and origin traceability of Tibetan yak meat using mid-infrared spectroscopy combined with multivariate analysis and machine learning
Enthalten in Journal of consumer protection and food safety 18.6.2025: 1-10
Online Ressource
Artikel 422 Large‐Scale Interlaboratory Study Along the Entire Process Chain of Laser Powder Bed Fusion: Bridging Variability, Standards, and Optimization across Metals and Polymers
Enthalten in Advanced engineering materials 17.06.2025. 22 S.
Online Ressource
Artikel 423 Multidimensional Engineering Strategies for Transition Metal Selenide Electrocatalysts in Water Electrolysis with Performance Optimization Mechanisms and Future Perspectives
Enthalten in The chemical record 17.06.2025. 18 S.
Online Ressource
Artikel 424 Phase Stability in Rare‐Earth‐Doped Apatites: A Machine Learning Approach
Enthalten in Advanced intelligent systems 17.06.2025. 8 S.
Online Ressource
Artikel 425 Spin Engineering of Dual‐Atom Site Catalysts for Efficient Electrochemical Energy Conversion
Enthalten in Advanced materials 17.06.2025. 47 S.
Online Ressource
Artikel 426 Exploring factors driving the evolution of chronic lesions in multiple sclerosis using machine learning
Enthalten in European radiology 17.6.2025: 1-10
Online Ressource
Artikel 427 Hybrid deep learning and machine learning framework for high-precision water quality prediction in urban systems
Enthalten in Environment, development and sustainability 17.6.2025: 1-20
Online Ressource
Artikel 428 Machine Learning Approach to Predict Corrosion Inhibition Performance of Amino Acid-Derivate Corrosion Inhibitor for Carbon Steel in Neutral Medium
Enthalten in Journal of materials engineering and performance 17.6.2025: 1-10
Online Ressource
Artikel 429 Machine learning for EMG-based gesture recognition in brain–computer interfaces and humanoid robots
Enthalten in International journal of intelligent robotics and applications 17.6.2025: 1-12
Online Ressource
Artikel 430 Predicting ultimate tensile and break strength of SLS PA 12 parts using machine learning on tensile load–displacement data
Enthalten in Progress in additive manufacturing 17.6.2025: 1-43
Online Ressource


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