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Showing results 1 to 10 of 6244 (Search time: 0.0 seconds).

Enhancing flow stress predictions in CoCrFeNiV high entropy alloy with conventional and machine learning techniquesoa mark
  • Dewangan, Sheetal Kumar;
  • Jain, Reliance;
  • Bhattacharjee, Soumyabrata;
  • Jain, Sandeep;
  • Paswan, Manikant;
  • Samal, Sumanta;
  • Ahn, Byungmin
  • 2024-05-01
  • Journal of Materials Research and Technology, Vol.30, pp.2377-2387
  • Elsevier Editora Ltda
Machine-learned wearable sensors for real-Time hand-motion recognition: Toward practical applicationsoa mark
  • Pyun, Kyung Rok;
  • Kwon, Kangkyu;
  • Yoo, Myung Jin;
  • Kim, Kyun Kyu;
  • Gong, Dohyeon;
  • Yeo, Woon Hong;
  • Han, Seungyong;
  • Ko, Seung Hwan
  • 2024-02-01
  • National Science Review, Vol.11
  • Oxford University Press
Bandgap analysis of transition-metal dichalcogenide and oxide via machine learning approach
  • 2022-12-01
  • Journal of Physics and Chemistry of Solids, Vol.171
  • Elsevier Ltd
Historical inference based on semi-supervised learningoa mark
  • 2018-09-15
  • Expert Systems with Applications, Vol.106, pp.121-131
  • Elsevier Ltd
Multilayered review of safety approaches for machine learning-based systems in the days of AI
  • 2021-06-01
  • Journal of Systems and Software, Vol.176
  • Elsevier Inc.
Machine learning-enhanced design of lead-free halide perovskite materials using density functional theory
  • Kumar, Upendra;
  • Kim, Hyeon Woo;
  • Maurya, Gyanendra Kumar;
  • Raj, Bincy Babu;
  • Singh, Sobhit;
  • Kushwaha, Ajay Kumar;
  • Cho, Sung Beom;
  • Ko, Hyunseok
  • 2025-01-01
  • Current Applied Physics, Vol.69, pp.1-7
  • Elsevier B.V.
EEG-based emotion classification for Alzheimer’s disease patients using conventional machine learning and recurrent neural network modelsoa mark
  • 2020-12-02
  • Sensors (Switzerland), Vol.20, pp.1-27
  • MDPI AG
Machine learning based quantitative consequence prediction models for toxic dispersion casualty
  • 2023-02-01
  • Journal of Loss Prevention in the Process Industries, Vol.81
  • Elsevier Ltd
Assessment of construction workers’ perceived risk using physiological data from wearable sensors: A machine learning approach
  • 2021-10-01
  • Journal of Building Engineering, Vol.42
  • Elsevier Ltd
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