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Showing results 1 to 10 of 2888 (Search time: 0.0 seconds).

Review on applications of artificial neural networks to develop high entropy alloys: A state-of-the-art technique
  • Dewangan, Sheetal Kumar;
  • Nagarjuna, Cheenepalli;
  • Jain, Reliance;
  • Kumawat, Rameshwar L.;
  • Kumar, Vinod;
  • Sharma, Ashutosh;
  • Ahn, Byungmin
  • 2023-12-01
  • Materials Today Communications, Vol.37
  • Elsevier Ltd
Deep learning models for quality estimation of gas tungsten arc welding
  • 2022-01-01
  • Welding International, Vol.36, pp.17-24
  • Taylor and Francis Ltd.
Prediction of nanoindentation creep behavior of tungsten-containing high entropy alloys using artificial neural network trained with Levenberg–Marquardt algorithm
  • Dewangan, Sheetal Kumar;
  • Sharma, Ashutosh;
  • Lee, Hansung;
  • Kumar, Vinod;
  • Ahn, Byungmin
  • 2023-10-05
  • Journal of Alloys and Compounds, Vol.958
  • Elsevier Ltd
Inverse-Based Approach to Explaining and Visualizing Convolutional Neural Networks
  • 2022-12-01
  • IEEE Transactions on Neural Networks and Learning Systems, Vol.33, pp.7318-7329
  • Institute of Electrical and Electronics Engineers Inc.
Prediction of issuance of emergency evacuation orders for chemical accidents using machine learning algorithm
  • 2018-11-01
  • Journal of Loss Prevention in the Process Industries, Vol.56, pp.162-169
  • Elsevier Ltd
Understanding and explaining convolutional neural networks based on inverse approach
  • 2023-01-01
  • Cognitive Systems Research, Vol.77, pp.142-152
  • Elsevier B.V.
Unsupervised feature learning for self-tuning neural networksoa mark
  • 2021-01-01
  • Neural Networks, Vol.133, pp.103-111
  • Elsevier Ltd
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