- István Szatmári, Ph.D., senior research fellow

István Szatmári received the M.Sc. degree in electrical engineering from the Technical University of Budapest, Hungary, in 1995 and the Ph.D. degree from the Hungarian Academy of Sciences in 2002. He is currently at the Analogical and Neural Computing Laboratory of the Computer and Automation Research Institute of the Hungarian Academy of Sciences. In 1997 and 2004, he worked at the University of California (Berkeley, USA) as a research assistant working on CNN projects related to real time image processing. His research interests include associative memories, theory of metrics, and hardware design hosting CNN-UM chips.
He is the author or co-author of more than 30 publications, out of these 8 were published in referred journals and 15 in conference proceedings. He is a co-author of the "Towards the Visual Microprocessor: VLSI Design and the Use of Cellular Neural Network Universal Machines" book from Wiley.
He received Bolyai János Hungarian State Fellowship (2000), and Hungarian State Eötvös Scholarship (1997). He is member of the IEEE.
In recent years he has participated in several successful research and development projects including US, European, Hungarian R&D grants. His development experience and competency includes mix mode (analog and digital) architecture design and measurement, multiprocessor Texas DSP environment, fast image processing algorithm development.
Publications[ order by time]
[ order by categories ]
[ order by authors]
- Topographic and non-topographic neural network based computational platform for UAV applications
- Cellular multiadaptive analogic achitecture: a computational framework for UAV applications
- Efficient off-line feature selection strategies for on-line classifier systems
- Feature guided visual attention with topographic array processing and neural network-based classification
- Multi-channel spatio-temporal topographic processing for visual search and navigation
- Bio-inspired flight control and visual search with CNN technology
- Adaptive multi-rate, multi-grid and multi-scale algorithms running on analogic architecture
- Classification of spatio-temporal features: the nearest neighbor family
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
Csapodi, M- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
Espejo, S- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
Fehér, B- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
- The new framework of applications: the Aladdin system
- Active wave computing on silicon: chip experiments
- Moving object traking on panoramic images.
- Analogic cellular PDE machines.
- Image processing library for the ALADDIN visual computer.
- Computing on silicon with trigger-waves: experiments on CNN-UM chips.
- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- An analogic CNN engine board with the 64x64 analog I/O CNN-UM chip.
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
Kozek, T- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- Morphology and autowave metric on CNN applied to Bubble-Debris classification.
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- An analogic CNN engine board with the 64x64 analog I/O CNN-UM chip.
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- A new learning algorithm to implement associative memory on CNN. (Research report of the Analogical and Neural Computing Laboratory DNS-8-1995.)
- A fast learning method to implement associative memory on CNN
Linán, G- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
László, K- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- A fast fixed point learning method to implement associative memory on CNN's.
- A fast learning method to implement associative memory of CNNs.(Research report of Analogical and Neural Computing Laboratory, DNS-9-1996.)
- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
Nemes, L- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
- Active wave computing on silicon: chip experiments
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- Topographic and non-topographic neural network based computational platform for UAV applications
- Cellular multiadaptive analogic achitecture: a computational framework for UAV applications
- Efficient off-line feature selection strategies for on-line classifier systems
- The new framework of applications: the Aladdin system
- Vision systems based on the 128x128 focal plane cellular visual microprocessor chips
- Feature guided visual attention with topographic array processing and neural network-based classification
- Multi-channel spatio-temporal topographic processing for visual search and navigation
- Bio-inspired flight control and visual search with CNN technology
- Adaptive multi-rate, multi-grid and multi-scale algorithms running on analogic architecture
- Active wave computing on silicon: chip experiments
- Classification of spatio-temporal features: the nearest neighbor family
- Analogic cellular PDE machines.
- Image processing library for the ALADDIN visual computer.
- Computing on silicon with trigger-waves: experiments on CNN-UM chips.
- Morphology and autowave metric on CNN applied to Bubble-Debris classification.
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- A nonlinear wave mertic and its CNN implementation for object classification.
- Spatio-temporal CNN algorithm for object segmentation and object recognition.
- Bubble-debris classification via binary morphology and autowave metric on CNN.
- Image segmentation and edge detection via constrained diffusion and adaptive morphology: a CNN approach to bubble/debris image enhancement.
Rodriguez-Vázquez, A- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- Multi-channel spatio-temporal topographic processing for visual search and navigation
- Analogic cellular PDE machines.
- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- Morphology and autowave metric on CNN applied to Bubble-Debris classification.
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- A nonlinear wave mertic and its CNN implementation for object classification.
- The CNN implementation of wave type metric for image analysis and classification.
- Spatio-temporal CNN algorithm for object segmentation and object recognition.
- Bubble-debris classification via binary morphology and autowave metric on CNN.
- Image segmentation and edge detection via constrained diffusion and adaptive morphology: a CNN approach to bubble/debris image enhancement.
- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
- High-speed label inspection system for textile industry
- Topographic and non-topographic neural network based computational platform for UAV applications
- Cellular multiadaptive analogic achitecture: a computational framework for UAV applications
- Efficient off-line feature selection strategies for on-line classifier systems
- The new framework of applications: the Aladdin system
- Vision systems based on the 128x128 focal plane cellular visual microprocessor chips
- Feature guided visual attention with topographic array processing and neural network-based classification
- Multi-channel spatio-temporal topographic processing for visual search and navigation
- Bio-inspired flight control and visual search with CNN technology
- Adaptive multi-rate, multi-grid and multi-scale algorithms running on analogic architecture
- Active wave computing on silicon: chip experiments
- Classification of spatio-temporal features: the nearest neighbor family
- Moving object traking on panoramic images.
- Analogic cellular PDE machines.
- Image processing library for the ALADDIN visual computer.
- Computing on silicon with trigger-waves: experiments on CNN-UM chips.
- Nonlinear wave metric for object comparison on CNN architecture.
- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- An analogic CNN engine board with the 64x64 analog I/O CNN-UM chip.
- The implementation of a nonlinear wave metric for image analysis and classification on the 64x64 I/O CNN-UM chip.
- Morphology and autowave metric on CNN applied to Bubble-Debris classification.
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- A nonlinear wave mertic and its CNN implementation for object classification.
- The CNN implementation of wave type metric for image analysis and classification.
- Spatio-temporal CNN algorithm for object segmentation and object recognition.
- A fast fixed point learning method to implement associative memory on CNN's.
- Bubble-debris classification via binary morphology and autowave metric on CNN.
- Image segmentation and edge detection via constrained diffusion and adaptive morphology: a CNN approach to bubble/debris image enhancement.
- A fast learning method to implement associative memory of CNNs.(Research report of Analogical and Neural Computing Laboratory, DNS-9-1996.)
- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
- A new learning algorithm to implement associative memory on CNN. (Research report of the Analogical and Neural Computing Laboratory DNS-8-1995.)
- A fast learning method to implement associative memory on CNN
- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
- A fast fixed point learning method to implement associative memory on CNN's.
- A fast learning method to implement associative memory of CNNs.(Research report of Analogical and Neural Computing Laboratory, DNS-9-1996.)
- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
- A new learning algorithm to implement associative memory on CNN. (Research report of the Analogical and Neural Computing Laboratory DNS-8-1995.)
- A fast learning method to implement associative memory on CNN
- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
Venetianer, PL- ACE: A digital floating point CNN emulator engine.
Authors: Fehér, B; Szolgay, P; Roska, T; Radványi, AG; Szirányi, T; Csapodi, M; László, K; Nemes, L; Szatmári, I; Tóth, G; Venetianer, PLDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1996.Published by: 1996 fourth IEEE international workshop on Cellular Neural Networks and their applications proceedings. CNNA-96. Seville, 1996. (Page: 273-278)
Zarándy, A- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- High-speed label inspection system for textile industry
- Topographic and non-topographic neural network based computational platform for UAV applications
- Cellular multiadaptive analogic achitecture: a computational framework for UAV applications
- The new framework of applications: the Aladdin system
- Vision systems based on the 128x128 focal plane cellular visual microprocessor chips
- Moving object traking on panoramic images.
- Image processing library for the ALADDIN visual computer.
- CNN technology in action.
Authors: Zarándy, Á; Espejo, S; Földesy, P; Kék, L; Linán, G; Rekeczky, C; Rodriguez-Vázquez, A; Roska, T; Szatmári, I; Szirányi, T; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Proceedings of the 6th IEEE international workshop on cellular neural networks and their applications. (CNNA 2000). Catania, 2000. (Page: 79-81)
- An analogic CNN engine board with the 64x64 analog I/O CNN-UM chip.
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
Zöld, S- A CNN application development environment and toolkit, CADETWin.
Authors: Roska, T; László, K; Kék, L; Kozek, T; Nemes, L; Rekeczky, C; Szatmári, I; Zarándy, A; Zöld, S; Szolgay, PDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 2000.Published by: Towards the visual microprocessor. VLSI design and the use of cellular neural network universal machines. (Page: 39-58)
- The computational infrastructure for cellular visual microprocessors.
Authors: Szolgay, P; Zarándy, Á; Zöld, S; Roska, T; Földesy, P; Kék, L; Kozek, T; László, K; Petrás, I; Rekeczky, CS; Szatmári, I; Bálya, DDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: MicroNeuro '99. Proceedings of the seventh international conference on microelectronics for neural, fuzzy, and bio-inspired systems. Granada, 1999. (Page: 54-60)
- The CADETWin application software design system - a tutorial.
Authors: Szolgay, P; László, K; Kék, L; Kozek, T; Nemes, L; Petrás, I; Rekeczky, CS; Szatmári, I; Zarándy, Á; Zöld, S; Roska, TDepartment: Cellular Sensory and Optical Wave Computing LaboratoryDate: 1999.Published by: Design automation day on cellular visual microprocessor. Stresa, 1999. (Page: 58-68)
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