Revista Raites

Referencias

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Burger, W., & Burge, M. J. (2022c). Digital Image Processing. En Texts in computer science. https://doi.org/10.1007/978-3-031-05744-1

Desu, R. K., Krishnamurthy, H. N., Balu, A., Gupta, A. K., & Singh, S. K. (2015). Mechanical properties of Austenitic Stainless Steel 304L and 316L at elevated temperatures. Journal Of Materials Research and Technology, 5(1), 13-20. https://doi.org/10.1016/j.jmrt.2015.04.001

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Ferreira, A., & Giraldi, G. (2017). Convolutional Neural Network approaches to granite tiles classification. Expert Systems with Applications, 84, 1-11. https://doi.org/10.1016/j.eswa.2017.04.053

Filho, P. P. R., Santos, J. C. D., Freitas, F. N. C., De Araújo Rodrigues, D., Ivo, R. F., Herculano, L. F. G., & De Abreu, H. F. G. (2017). New approach to evaluate a non-grain oriented electrical steel electromagnetic performance using photomicrographic analysis via digital image processing. Journal Of Materials Research And Technology, 8(1), 112-126. https://doi.org/10.1016/j.jmrt.2017.09.007

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Mohamed, Y. S., Shehata, H. M., Abdellatif, M., & Awad, T. H. (2019). Steel crack depth estimation based on 2D images using artificial neural networks. Alexandria Engineering Journal, 58(4), 1167-1174. https://doi.org/10.1016/j.aej.2019.10.001

Sedriks, A., & Zaroog, O. (2017). Corrosion of Stainless Steels. En Elsevier eBooks. https://doi.org/10.1016/b978-0-12-803581-8.02893-9

Thankachan, T., Prakash, K. S., Malini, R., Ramu, S., Sundararaj, P., Rajandran, S., Rammasamy, D., & Jothi, S. (2018). Prediction of surface roughness and material removal rate in wire electrical discharge machining on aluminum-based alloys/composites using Taguchi coupled Grey Relational Analysis and Artificial Neural Networks. Applied Surface Science, 472, 22-35. https://doi.org/10.1016/j.apsusc.2018.06.117

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Woldaregay, A. Z., Årsand, E., Walderhaug, S., Albers, D., Mamykina, L., Botsis, T., & Hartvigsen, G. (2019). Data-driven modeling and prediction of blood glucose dynamics: Machine learning applications in type 1 diabetes. Artificial Intelligence in Medicine, 98, 109-134. https://doi.org/10.1016/j.artmed.2019.07.007