Grupo ISIS - Publication - Convolutional neural network learning versus traditional segmentation for the approximation of the degree of defective surface in titanium for implantable medical devices

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Convolutional neural network learning versus traditional segmentation for the approximation of the degree of defective surface in titanium for implantable medical devices

BibTex:
Research Area:	Inteligencia Computacional	Year:	2019
Type of Publication:	Proceedings
Authors:	Stoean, Ruxandra; Stoean, Catalin; Samide, Adriana; Joya Caparrós, Gonzalo


Address:	Gran Canarias, Islas Canarias (Spain)
Month:	June 12-14


@proceedings{Rux/Con/2019, author = "Ruxandra Stoean and Catalin Stoean and Adriana Samide and Joya Caparr{\'o}s, Gonzalo", address = "Gran Canarias, Islas Canarias (Spain)", doi = "https://doi.org/10.1007/978-3-030-20521-8_71", month = "June 12-14 ", title = "{C}onvolutional neural network learning versus traditional segmentation for the approximation of the degree of defective surface in titanium for implantable medical devices", year = "2019", }
Comments:	15th International Work-Conference on Artificial Neural Networks (IWANN 2019)
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