David Iclanzan
Citado por
Citado por
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
Low and high grade glioma segmentation in multispectral brain MRI data
L Szilágyi, D Iclanzan, Z Kapás, Z Szabó, A Gyorfi, L Lefkovits
Acta Universitatis Sapientiae, Informatica 10 (1), 110-132, 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
Automatic detection of hard and soft exudates from retinal fundus images
B Borsos, L Nagy, D Iclanzan, L Szilágyi
Acta Unitiversitatis Sapientiae-Informatica 11 (1), 65-79, 2019
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
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
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, ...
Pacific-Rim Symposium on Image and Video Technology, 137-149, 2017
A review on suppressed fuzzy c-means clustering models
L Szilágyi, L Lefkovits, D Iclanzan
Acta Universitatis Sapientiae Informatica 12 (2), 302-324, 2020
Impact of instructor on-slide presence in synchronous e-learning
Z Katai, D Iclanzan
Education and Information Technologies 28 (3), 3089-3115, 2023
Brain tumor segmentation from multi-spectral MR image data using random forest classifier
S Csaholczi, D Iclănzan, L Kovács, L Szilágyi
International Conference on Neural Information Processing, 174-184, 2020
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
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
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
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
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
Iberoamerican Congress on Pattern Recognition, 375-384, 2019
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
Evolving computationally efficient hashing for similarity search
D Iclanzan, SM Szilágyi, L Szilágyi
Neural Information Processing: 25th International Conference, ICONIP 2018 …, 2018
Cell state change dynamics in cellular automata
D Iclănzan, A Gog, C Chira
Memetic Computing 5, 131-139, 2013
Hierarchical allelic pairwise independent functions
D Iclanzan
Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011
GeCiM: a novel generalized approach to c-means clustering
L Szilágyi, D Iclănzan, SM Szilágyi, D Dumitrescu
Progress in Pattern Recognition, Image Analysis and Applications: 13th …, 2008
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