ROBERTO FERNANDEZ MARTINEZ-rekin lankidetzan egindako argitalpenak (12)

2023

  1. The determination of optimum segmentation parameters using genetic algorithms: Application to different segmentation algorithms and transmission electron microscopy tomography reconstructed volumes

    Microscopy Research and Technique, Vol. 86, Núm. 10, pp. 1237-1248

2021

  1. Quantitative electron tomography of polylactic acid/clay nanocomposites for better comprehension of processing–microstructure–elastic modulus

    Polymers and Polymer Composites, Vol. 29, Núm. 6, pp. 724-732

2019

  1. Use of support vector machines, neural networks and genetic algorithms to characterize rubber blends by means of the classification of the carbon black particles used as reinforcing agent

    Soft Computing, Vol. 23, Núm. 15, pp. 6115-6124

2018

  1. Influence of cryogenic treatment on wear resistance and microstructure of AISI A8 tool steel

    Metals, Vol. 8, Núm. 12

  2. Semi-automated quantification of the microstructure of PLA/clay nanocomposites to improve the prediction of the elastic modulus

    Polymer Testing, Vol. 66, pp. 280-291

2017

  1. Carbide distribution based on automatic image analysis for cryogenically treated tool steels

    Materiali in Tehnologije, Vol. 51, Núm. 4, pp. 609-611

  2. Methodology to classify the shape of reinforcement fillers: optimization, evaluation, comparison, and selection of models

    Journal of Materials Science, Vol. 52, Núm. 1, pp. 569-580

  3. Tensile strength prediction of rubber blends using linear regression techniques

    IEEE 4th International Conference on Soft Computing and Machine Intelligence, ISCMI 2017

2015

  1. 3D TEM reconstruction and segmentation process of laminar bio-nanocomposites

    AIP Conference Proceedings

  2. Pin on disk against ball on disk for the evaluation of wear improvement on cryo-treated metal cutting shears

    AIP Conference Proceedings

2014

  1. Modeling of the mechanical properties of carbon-black reinforced rubber blends by machine learning techniques

    Applied Mechanics and Materials

  2. Use of decision tree models based on evolutionary algorithms for the morphological classification of reinforcing nano-particle aggregates

    Computational Materials Science, Vol. 92, pp. 102-113