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Analysis of Multidimensional neural Activity Via CNN-UM

International Journal of neural Systems 2003年第6期13卷 479-487页

作者： Gal, Viktor Grun, Sonja Tetzlaff, Ronald Analogical and Neural Computing Laboratory Hungarian Academy of Sciences Computer Automation Research Institute Ldgymdnyosi u. 13 BudapestH-1111 Hungary Dept. Neurophysiology Max Planck Inst for Brain Research Deutschordnerstr. 46 Frankfurt/MainD-60528 Germany Institute for Applied Physics University of Frankfurt Robert-Mayer-Str. 2-4 Frankfurt/MainD-60325 Germany

In this paper we show that the Cellular Nonlinear Network Universal Machine (CNN-UM) is an excellent tool for analyzing time series of multidimensional binary signals. The developed algorithm is dedicated to process electrophysiological multi-neuron recordings: our aim is to find specific multidimensional activity patterns, which may reflect higher order functional cell-assemblies. The analysis consists of two parts: first, the occurrences of different patterns are counted, then the statistical significance of each occurrence frequency is calculated separately. © 2003 World Scientific Publishing Company.

关键词： Electrophysiology

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Picture segmentation with introducing an anisotropic preliminary step to an MRF model with cellular neural networks

Picture segmentation with introducing an anisotropic prelimi...

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13th International Conference on Pattern Recognition, ICPR 1996

作者： Szirányi, Tamás Czúni, László Department of Image Processing and Neurocomputing University of Veszprém 8200 Veszprém Egyetem út 10. Hungary Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences Kende u. 13-17 H- 1111 Budapest Hungary

ISBN: (纸本)081867282X

Due to the large computation power needed for Markovian random field (MRF) based image processing, new variations of the basic MRF model are implemented. The transportation of the model to the very fast cellular neural networks (CNN) gave new tasks and opportunities to improve the technique, since the CNN has a special local architecture. This CNN architecture can be implemented in real VLSI circuits of superior speed in image processing. A type of MRF image segmentation with modified metropolis dynamics (MMD) can be well implemented in the CNN architecture. In this paper we address the improvement of this existing CNN method by introducing anisotropic diffusion as the smoothing process in the model. We suggest that this new feature with the MRF representation will give a new approach to solving early vision problems in the future. © 1996 IEEE.

关键词： Cellular neural networks

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computing on silicon with trigger waves: Experiments on CNN-UM chips

Computing on silicon with trigger waves: Experiments on CNN-...

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2001 IEEE International Symposium on Circuits and Systems, ISCAS 2001

作者： Rekeczky, Csaba Szatmari, Istvan Foldesy, Peter Analogical and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences Kende U. 13-17 Budapest 1111 Hungary Jedlik Laboratories Department of Information Technology Peter Pazmany Catholic University Szentkirdyi U. 28 Budapest 1088 Hungary

ISBN: (纸本)0780366859

In this paper, experimental results on Cellular neural Network Universal Machine (CNN-UM) chips will be presented. These analogic spatio-temporal visual microprocessors make it possible that one can use nonlinear waves as the basic kernels of algorithms solving filtering-reconstruction and/or detection-classification problems. Showing output results from series of experiments it will be demonstrated how trigger waves, the simplest nonlinear waves, can constructively be used in a number of important application areas. © 2001 IEEE.

关键词： Silicon

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CNN technology in action

CNN technology in action

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： A. Zarandy S. Espejo P. Foldesy L. Kek G. Linan C. Rekeczky A. Rodriguez-Vazquez T. Roska I. Szatmari T. Sziranyi P. Szolgay Analogical and Neural Computing Laboratory of the Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Hungary Institute of Microelectronics of Seville Spanish National Microelectronics Center Spain

Two Cellular neural Net Universal Machine (CNN-UM) prototypes are demonstrated in action. The first one is the latest 4096 cell-processor, analog I/O, analogic CNN visual microprocessor, on which online video image processing will be performed. The second one, the 20/spl times/22 binary input-binary output CNN-UM chip is introduced as an ultra high-speed focal plane array processor. In the live demonstration it captures and classifies 10000 frames in a second.

关键词： Cellular neural networks Microelectronics Microprocessors Image processing Prototypes Laboratories Engines Condition monitoring Cellular networks Logic

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Hand gesture recognition in camera-projector system

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8th European Conference on computer Vision, ECCV 2004 and International Workshop on Human-computer Interaction, HCI 2004

作者： Licsár, Attila Szirányi, Tamás University of Veszprém Department of Image Processing and Neurocomputing Egyetem u. 10 VeszprémH-8200 Hungary Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Kendeu. 13-17 BudapestH-1111 Hungary

ISBN: (纸本)3540220127

Our paper proposes a vision-based hand gesture recognition system. It is implemented in a camera-projector system to achieve an augmented reality tool. In this configuration the main problem is that the hand surface reflects the projected background, thus we apply a robust hand segmentation method. Hand localizing is based on a background subtraction method, which adapts to the changes of the projected background. Hand poses are described by a method based on modified Fourier descriptors, which involves distance metric for the nearest neighbor classification. The proposed classification method is compared to other feature extraction methods. We also conducted tests on several users. Finally, the recognition efficiency is improved by the recognition probabilities of the consecutive detected gestures by maximum likelihood approach. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Augmented reality

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Anisotropic diffusion as a preprocessing step for efficient image compression

Anisotropic diffusion as a preprocessing step for efficient ...

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International Conference on Pattern Recognition

作者： T. Sziranyi I. Kopilovic B.P. Toth Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary Department of Image Processing & Neurocomputing University of Veszprem Veszprem Hungary

Anisotropic diffusion is an image enhancement method. It is a nonlinear process which removes noise and irrelevant details while preserving the edges, i.e. it "extracts" the essential visual information. The paper proposes a useful application of anisotropic diffusion in image data compression. We argue that for high compression an anisotropic diffusion preprocessing results in better quality of the decoded image.

关键词： Anisotropic magnetoresistance Image coding Image processing Transform coding Space heating Equations Laboratories automation Time of arrival estimation Data mining

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A CNN solution for depth estimation from binocular stereo imagery

A CNN solution for depth estimation from binocular stereo im...

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IEEE International Workshop on Cellular Nanoscale Networks and their Applications, (CNNA)

作者： A.G. Radvanyi T. Kozek L.O. Chua Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Eleclronics Research Laboratory University of California Berkeley CA USA

Novel results and experiments are presented on the application of cellular neural networks to binocular stereo vision. A cellular neural network (CNN) universal machine (UM) algorithm is described for depth estimation as part of a stereo-vision-based guidance system for autonomous vehicles. Being most amenable to revealing stereo correspondence, extraction of vertical edges is performed first. Then their distance from the observer in 3D space is established through a stereo matching scheme. The performance of the algorithm is demonstrated on real-life highway imagery and it is shown that very low latency real-time operation is attainable via the CNN-UM.

关键词： Cellular neural networks Image edge detection computer vision Remotely operated vehicles Mobile robots Image segmentation Automated highways computer networks Laboratories Electronic mail

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Implementing a retinal visual language in CNN: a neuromorphic study

Implementing a retinal visual language in CNN: a neuromorphi...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： F. Werblin B. Roska D. Balya C. Rekeczky T. Roska Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary Department of Molecular and Cell Biology University of California at Berkeley Berkeley CA USA

ISBN: (纸本)0780366859

The retina sends to the brain a parallel set of about a dozen different space-time representations of the visual world. Each of these representations is generated by a distinct set of "feature detecting" transformations. These features most likely contain all the information we need and use to analyze and interpret the visual world. They constitute a fundamental visual language that is elaborated upon at higher centers in the brain. A multi-layer CNN is presented for mimicking this new retinal model. The model is composed of several prototype 3-layer CNN units, called Complex R-units. Surfaces of activity are represented by CNN layers. Various parameter sets represent the different parts of the multi-layer retinal model. The whole model can be described by a visual language with elementary instructions of a CNN Universal Machine containing the programmable Complex R-units. Decomposition methods in time and space are discussed.

关键词： Retina Cellular neural networks Neuromorphics computer vision Information analysis Laboratories Biology computing Concurrent computing Turing machines Image analysis

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Picture segmentation with introducing an anisotropic preliminary step to an MRF model with cellular neural networks

Picture segmentation with introducing an anisotropic prelimi...

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International Conference on Pattern Recognition

作者： T. Sziranyi L. Czuni Analogical and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Department of Image Processing and Neurocomputing University of Veszprém Hungary

关键词： Anisotropic magnetoresistance Cellular neural networks Image segmentation Image processing computer networks Pixel Labeling Smoothing methods Laboratories automation

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Supervised training based hand gesture recognition system

Supervised training based hand gesture recognition system

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作者： Licsár, Attila Szirányi, Tamás University of Veszprém Department of Image Processing and Neurocomputing Egyetem u. 10 H-8200 Veszprém Hungary Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Kende u. 13-17 H-1111 Budapest Hungary

We have developed a hand gesture recognition system, based on the shape analysis of static gestures, for Human computer Interaction purposes. Our appearance-based recognition uses modified Fourier descriptors for the classification, of hand shapes. As always found in literature, such recognition systems consist of two phases: training and recognition. In our new practical approach, following the chosen appearance-based model, training and recognition is done in an interactive supervised way: the adaptation for untrained gestures is also solved by hand signals. Our experimental results with three different users are reported. In this paper, besides describing the recognition itself, we demonstrate our interactive training method in a practical application. © 2002 IEEE.

关键词： Gesture recognition

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