Overcoming hierarchical difficulty by hill-climbing the building block structure D Iclanzan, D Dumitrescu Proceedings of the 9th annual conference on Genetic and evolutionary …, 2007 | 41 | 2007 |
Low and high grade glioma segmentation in multispectral brain MRI data L Szilágyi, D Iclănzan, Z Kapás, Z Szabó, Á Győrfi, L Lefkovits Acta Universitatis Sapientiae, Informatica 10 (1), 110-132, 2018 | 20 | 2018 |
Data-driven local optima network characterization of QAPLIB instances D Iclanzan, F Daolio, M Tomassini Proceedings of the 2014 Annual Conference on Genetic and Evolutionary …, 2014 | 20 | 2014 |
Complex systems and cellular automata models in the study of complexity C Chira, A Gog, RI Lung, D Iclanzan Stud Inform Ser 55, 33-49, 2010 | 18 | 2010 |
Automatic detection of hard and soft exudates from retinal fundus images B Borsos, L Nagy, D Iclănzan, L Szilágyi Acta Universitatis Sapientiae, Informatica 11 (1), 65-79, 2019 | 15 | 2019 |
Evolutionary detection of community structures in complex networks: A new fitness function C Chira, A Gog, D Iclănzan 2012 IEEE Congress on Evolutionary Computation, 1-8, 2012 | 15 | 2012 |
Automatic brain tumor segmentation in multispectral MRI volumes using a random forest approach Z Kapás, L Lefkovits, D Iclănzan, Á Győrfi, BL Iantovics, S Lefkovits, ... Image and Video Technology: 8th Pacific-Rim Symposium, PSIVT 2017, Wuhan …, 2018 | 8 | 2018 |
A study on histogram normalization for brain tumour segmentation from multispectral MR image data Á Győrfi, Z Karetka-Mezei, D Iclănzan, L Kovács, L Szilágyi Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2019 | 7 | 2019 |
Automatic brain tumor segmentation in multispectral MRI volumetric records L Szilágyi, L Lefkovits, B Iantovics, D Iclănzan, B Benyó Neural Information Processing: 22nd International Conference, ICONIP 2015 …, 2015 | 7 | 2015 |
A generalized c-means clustering model using optimized via evolutionary computation L Szilágyi, D Iclanzan, SM Szilagyi, D Dumitrescu, B Hirsbrunner 2009 IEEE International Conference on Fuzzy Systems, 451-455, 2009 | 7 | 2009 |
Efficient 3D curve skeleton extraction from large objects L Szilágyi, SM Szilágyi, D Iclănzan, L Szabó Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2011 | 6 | 2011 |
Intensity inhomogeneity correction and segmentation of magnetic resonance images using a multi-stage fuzzy clustering approach SM Szilágyi, L Szilágyi, D Iclanzan, L Dávid, A Frigy, Z Benyó Neural Network World 19 (5), 513-528, 2009 | 6 | 2009 |
Going for the big fishes: Discovering and combining large neutral and massively multimodal building-blocks with model based macro-mutation D Iclanzan, D Dumitrescu Proceedings of the 10th annual conference on Genetic and evolutionary …, 2008 | 6 | 2008 |
Evolving computationally efficient hashing for similarity search D Iclanzan, SM Szilágyi, L Szilágyi Neural Information Processing: 25th International Conference, ICONIP 2018 …, 2018 | 5 | 2018 |
Cell state change dynamics in cellular automata D Iclănzan, A Gog, C Chira Memetic Computing 5, 131-139, 2013 | 5 | 2013 |
Hierarchical allelic pairwise independent functions D Iclanzan Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011 | 5 | 2011 |
A review on suppressed fuzzy c-means clustering models L Szilágyi, L Lefkovits, D Iclanzan ACTA UNIVERSITATIS SAPIENTIAE INFORMATICA 12 (2), 302-324, 2020 | 4 | 2020 |
Brain tumor segmentation from multi-spectral MR image data using random forest classifier S Csaholczi, D Iclănzan, L Kovács, L Szilágyi Neural Information Processing: 27th International Conference, ICONIP 2020 …, 2020 | 4 | 2020 |
An Efficient Approach to Intensity Inhomogeneity Compensation Using c-Means Clustering Models L Szilágyi, D Iclănzan, L Crăciun, SM Szilágyi Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2011 | 4 | 2011 |
Learning inherent networks from stochastic search methods D Iclănzan, F Daolio, M Tomassini Evolutionary Computation in Combinatorial Optimisation: 14th European …, 2014 | 3 | 2014 |