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Citation: C. Rekeczky et al., The network behind spatio-temporal patterns: building low-complexity retinal models in CNN based on morphology, pharmacology and physiology, INT J CIRCU, 29(2), 2001, pp. 197-239

Authors: Szatmari, I Schultz, A Rekeczky, C Kozek, T Roska, T Chua, LO

Citation: I. Szatmari et al., Morphology and autowave metric on CNN applied to bubble-debris classification, IEEE NEURAL, 11(6), 2000, pp. 1385-1393

Authors: Rekeczky, C Chua, LO

Citation: C. Rekeczky et Lo. Chua, Computing with front propagation: Active contour and skeleton models in continuous-time CNN, J VLSI S P, 23(2-3), 1999, pp. 373-402

Authors: Szatmari, I Rekeczky, C Roska, T

Citation: I. Szatmari et al., A nonlinear wave metric and its CNN implementation for object classification, J VLSI S P, 23(2-3), 1999, pp. 437-447

Authors: Chandler, B Rekeczky, C Nishio, Y Ushida, A

Citation: B. Chandler et al., Adaptive simulated annealing in CNN template learning, IEICE T FUN, E82A(2), 1999, pp. 398-402

Authors: Rekeczky, C Tahy, A Vegh, Z Roska, T

Citation: C. Rekeczky et al., CNN-based spatio-temporal nonlinear filtering and endocardial boundary detection in echocardiography, INT J CIRCU, 27(1), 1999, pp. 171-207