 | 2011 |
| 19 |  | M. Alper Selver,
Cüneyt Güzelis:
Multilevel Data Classification and Function Approximation Using Hierarchical Neural Networks.
Computational Methods for the Innovative Design of Electrical Devices 2011: 147-166 |
| 2010 |
| 18 |  | Felix Fischer,
M. Alper Selver,
Walter Hillen,
Cüneyt Güzelis:
Integrating segmentation methods from different tools into a visualization program using an object-based plug-in interface.
IEEE Transactions on Information Technology in Biomedicine 14(4): 923-934 (2010) |
| 2009 |
| 17 |  | M. Alper Selver,
Cüneyt Güzelis:
Semiautomatic Transfer Function Initialization for Abdominal Visualization Using Self-Generating Hierarchical Radial Basis Function Networks.
IEEE Trans. Vis. Comput. Graph. 15(3): 395-409 (2009) |
| 2008 |
| 16 |  | M. Alper Selver,
Aykut Kocaoglu,
Güleser K. Demir,
Hatice Dogan,
Oguz Dicle,
Cüneyt Güzelis:
Patient oriented and robust automatic liver segmentation for pre-evaluation of liver transplantation.
Comp. in Bio. and Med. 38(7): 765-784 (2008) |
| 2007 |
| 15 |  | Gülay Büyükaksoy Kaplan,
Neslihan Serap Sengör,
Hakan Gürvit,
Cüneyt Güzelis:
Modelling the Stroop effect: A connectionist approach.
Neurocomputing 70(7-9): 1414-1423 (2007) |
| 2006 |
| 14 |  | Nurettin Acir,
Özcan Özdamar,
Cüneyt Güzelis:
Automatic classification of auditory brainstem responses using SVM-based feature selection algorithm for threshold detection.
Eng. Appl. of AI 19(2): 209-218 (2006) |
| 13 |  | Gülay Büyükaksoy Kaplan,
Neslihan Serap Sengör,
Hakan Gürvit,
Ibrahim Genç,
Cüneyt Güzelis:
A composite neural network model for perseveration and distractibility in the Wisconsin card sorting test.
Neural Networks 19(4): 375-387 (2006) |
| 2005 |
| 12 |  | Aysegül Uçar,
Yakup Demir,
Cüneyt Güzelis:
A New Formulation for Classification by Ellipsoids.
TAINN 2005: 100-106 |
| 11 |  | Mehmet Kerem Müezzinoglu,
Cüneyt Güzelis,
Jacek M. Zurada:
An energy function-based design method for discrete hopfield associative memory with attractive fixed points.
IEEE Transactions on Neural Networks 16(2): 370-378 (2005) |
| 10 |  | Nurettin Acir,
Cüneyt Güzelis:
Automatic recognition of sleep spindles in EEG via radial basis support vector machine based on a modified feature selection algorithm.
Neural Computing and Applications 14(1): 56-65 (2005) |
| 2004 |
| 9 |  | Nurettin Acir,
Cüneyt Güzelis:
An Application of Support Vector Machine in Bioinformatics: Automated Recognition of Epileptiform Patterns in EEG Using SVM Classifier Designed by a Perturbation Method.
ADVIS 2004: 462-471 |
| 8 |  | Nurettin Acir,
Cüneyt Güzelis:
Automatic recognition of sleep spindles in EEG by using artificial neural networks.
Expert Syst. Appl. 27(3): 451-458 (2004) |
| 7 |  | Mehmet Kerem Müezzinoglu,
Cüneyt Güzelis:
A Boolean Hebb rule for binary associative memory design.
IEEE Transactions on Neural Networks 15(1): 195-202 (2004) |
| 6 |  | Mehmet Kerem Müezzinoglu,
Cüneyt Güzelis:
Associative Memory Design via Path Embedding into a Graph.
Neural Processing Letters 19(3): 205-209 (2004) |
| 2003 |
| 5 |  | Aysegül Uçar,
Yakup Demir,
Cüneyt Güzelis:
Fuzzy Model Identification Using Support Vector Clustering Method.
ICANN 2003: 225-233 |
| 4 |  | Hatice Dogan,
Cüneyt Güzelis:
A Gradient Network for Vector Quantization and Its Image Compression Applications.
ICANN 2003: 554-561 |
| 3 |  | Mehmet Kerem Müezzinoglu,
Cüneyt Güzelis,
Jacek M. Zurada:
A new design method for the complex-valued multistate Hopfield associative memory.
IEEE Transactions on Neural Networks 14(4): 891-899 (2003) |
| 2000 |
| 2 |  | Zekeriya Uykan,
Cüneyt Güzelis,
Mehmet Ertugrul Çelebi,
Heikki N. Koivo:
Analysis of input-output clustering for determining centers of RBFN.
IEEE Trans. Neural Netw. Learning Syst. 11(4): 851-858 (2000) |
| 1995 |
| 1 |  | Bilge Günsel,
Cüneyt Güzelis:
Supervised learning of smoothing parameters in image restoration by regularization under cellular neural networks framework.
ICIP 1995: 470-473 |