SHS Web Conf.
Volume 144, 20222022 International Conference on Science and Technology Ethics and Human Future (STEHF 2022)
|Number of page(s)||4|
|Section||Application of Artificial Intelligence Technology and Machine Learning Algorithms|
|Published online||26 August 2022|
- Rumelhart, D., Hinton, G. & Williams, R. Learning representations by back-propagating errors. Nature 323, 533–536 (1986). https://doi.org/10.1038/323533a0 [Google Scholar]
- S. Chalup and F. Maire, “A Study on Hill Climbing Algorithms for Neural Network Training”, Proceedings of the 1999 Congress on Evolutionary Computation (CEC’99) July 6–9 1999, vol. 3, pp. 2014-2021, 1999. [Google Scholar]
- P. Cortez, A. Cerdeira, F. Almeida, T. Matos and J. Reis. Modeling wine preferences by data mining from physicochemical properties. In Decision Support Systems, Elsevier, 47(4):547-553, 2009. https://archive.ics.uci.edu/ml/datasets/wine+quality [CrossRef] [Google Scholar]
- Agarap, A. F. (2018). Deep learning using rectified linear units (relu). arXiv preprint arXiv:1803.08375. [Google Scholar]
- N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller and E. Teller, “Equation of state calculations by fast computing machines” in J. of Chem. Phys., vol. 21, no. 6, pp. 1087-1092, 1953. [CrossRef] [Google Scholar]
- Taha, A.A., Hanbury, A. Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool. BMC Med Imaging 15, 29 (2015). https://doi.org/10.1186/s12880-015-0068-x [CrossRef] [Google Scholar]
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