73 citations · 288 across the 10 of their papers we have counts for
3 papers · 1 filter
Characterizing unstructured data with the nearest neighbor permutation entropy
Leonardo G. J. M. Voltarelli, Arthur A. B. Pessa, Luciano Zunino +4
Permutation entropy and its associated frameworks are remarkable examples of physics-inspired techniques adept at processing complex and extensive datasets. Despite substantial pro…
Determining liquid crystal properties with ordinal networks and machine learning
Arthur A. B. Pessa, Rafael S. Zola, Matjaz Perc +1
Machine learning methods are becoming increasingly important for the development of materials science. In spite of this, the use of image analysis in the development of these syste…
Estimating physical properties from liquid crystal textures via machine learning and complexity-entropy methods
H. Y. D. Sigaki, R. F. de Souza, R. T. de Souza +2
Imaging techniques are essential tools for inquiring a number of properties from different materials. Liquid crystals are often investigated via optical and image processing method…