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Supervised and unsupervised art-like classifications of binary vectors on the CNN universal machine

Supervised and unsupervised art-like classifications of bina...

引用

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

作者： D. Balya T. Roska Analogical & Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary

Fast and robust classification of feature vectors is a crucial task in a number of real-time systems. A cellular neural/nonlinear network universal machine (CNN-UM) can be applied very efficiently as a feature detector and also for post-processing the results for object recognition. This paper shows how a robust classification scheme based on adaptive resonance theory (ART) can also be mapped to the CNN-UM. The designed analogic CNN algorithm is capable of classifying the extracted binary feature vectors keeping the advantages of the ART networks. An analogic algorithm is presented for unsupervised classification with tunable sensitivity and automatic new class creation. Another CNN-UM algorithm is suggested for supervised classification. In addition to the two algorithms, a new "repair" function is proposed to reduce the number of the created classes. The presented binary feature vector classification is feasible on the existing standard CNN-UM chips.

关键词： Cellular neural networks Turing machines Robustness Subspace constraints Real time systems Cellular networks computer vision Object detection Detectors Object recognition

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Multi-target tracking with stored program adaptive CNN universal machines

Multi-target tracking with stored program adaptive CNN unive...

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

作者： C. Rekeczky G. Timar G. Cserey Analogical and Neural Computing Systems Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

This paper shows that the performance of multi-target tracking (MTT) systems can be significantly increased with stored program adaptive cellular array sensors. The primary motivation of the present work is to define a topographic microprocessor architecture for MTT with embedded sensors capable of operating in a process real-time manner. In the ongoing experiments it is assumed that the input data flow is acquired by a single array sensor and the data is processed on an adaptive CNN-UM architecture consisting of both a cellular nonlinear network (CNN) and digital signal processing (DSP) microprocessors. The algorithms designed for this combined hardware platform use adaptive multi-channel CNN solutions for instantaneous position estimation and morphological characterization of all visible targets and the DSP environment for distance calculation, gating, data association, track maintenance and dynamic target motion prediction. A special feature of the architecture is that it allows interactive communication between the sensor and the digital environment. The configuration of functional modules for various real-time applications is discussed. Using real-life video-flows, successful tracking of several maneuvering targets is demonstrated within the proposed adaptive multi-channel framework.

关键词： Cellular neural networks Turing machines Sensor arrays Digital signal processing Adaptive arrays Microprocessors Sensor phenomena and characterization Target tracking Sensor systems Cellular networks

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Configurable multi-layer CNN-UM emulator on FPGA

Configurable multi-layer CNN-UM emulator on FPGA

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

作者： Z. Nagy P. Szolgay Department of lmage Processing and Neurocomputing University of Veszprém Veszprem Hungary Analogic and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Budapest Hungary

A new emulated digital multi-layer CNN-UM chip architecture called Falcon has been developed. In this paper the main steps of the FPGA implementation are introduced. Main results are as follows: CNN-UM architecture emulated on Xilinx Virtex series FPGA, 3D non-linear spatio-temporal dynamics can be implemented on this architecture. The critical parameters of the implementation in single layer configuration are 55 million cell update/second/processor core or equivalently 1 GOPS computing performance. In face of the high performance the power requirements of the architecture are relatively low only /spl sim/3 W per processor core. Using re-configurable devices to implement emulated digital architectures provides more flexibility compared to the custom VLSI designs because different Falcon architectures can be used on the same FPGA device.

关键词： Field programmable gate arrays Cellular neural networks Equations computer architecture Very large scale integration Signal processing Analog computers State feedback Laboratories Turing machines

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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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Supervised training based hand gesture recognition system

Supervised training based hand gesture recognition system

引用

International Conference on Pattern Recognition

作者： A. Licsar T. Sziranyi Department of Image Processing and Neurocomputing University of Veszprém Veszprem Hungary Analogical & Neural Computing Laboratory Computer & Automation Research Institute Hungarian Academy of Sciences (ATOMKI) 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. Besides describing the recognition itself we demonstrate our interactive training method in a practical application.

关键词： Shape Character recognition Image processing Laboratories automation Human computer interaction Application software Control systems Virtual environment Cameras

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Short circuit detection on printed circuit boards during the manufacturing process by using an analogic CNN algorithm 14th

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14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert systems, IEA/AIE 2001

作者： Hidvégi, Timót Szolgay, Péter Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O.B 63 BudapestH-1502 Hungary

ISBN: (纸本)3540422196

One of the most critical errors is the short circuit in the manufacturing of printed circuit boards. In this contribution we extend the already existing solution to more general cases where the errors can be detected by checking two production layers. The algorithm was tested with software simulator and 64*64 CNN-UM chip of ALADDIN System. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Printed circuit boards

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High speed stand-alone visual decision maker device based on focal plane analogic processor array chip

High speed stand-alone visual decision maker device based on...

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IEEE International Workshop on Virtual and Intelligent Measurement systems

作者： L. Torok A. Zarandy T. Roska Analogical & Neural Computing Systems Laboratory at Computer and Automation Research Institute of the Hungarian Academy of Sciences Budapest Hungary

ISBN: (纸本)0780365682

Newly emerging problems require high speed decision making based on visual perception of the environment. A project was set up to construct an intelligent agent like self-contained device that is capable to act in real-time and show collaborative behavior. Giving the hardware basis for decisions to be made a cellular nonlinear network CNN (Chua and Yang, 1988) chip implementation's optical input is used in combination with the cooperative devices' information that is received via binary ports and serial ports. The proposed design is a self-contained compact device that is prepared to operate stand-alone for up to 10 hours running on medium sized batteries while doing measurements, logging and collaborating with its environment via parallel port (for image transfer), RS-232 port (using modbus, profibus, PPP protocols) and binary I/O-s. Intelligent power module, optical isolation, watch dog capability is also considered.

关键词： Collaboration High speed optical techniques Nonlinear optics Decision making Visual perception Intelligent agent Hardware Cellular networks Cellular neural networks Nonlinear optical devices

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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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2001 IEEE International Symposium on Circuits and systems, ISCAS 2001

作者： Werblin, F. Roska, B. Balya, D. Rekeczky, C. Roska, T. Vision Research Laboratory Department of Molecular and Cell Biology University of California at Berkeley Berkeley CA-94720 United States Analogical and Neural Computing Laboratory Computer and Automation Research Institute Lagymanyosi U. 11 Budapest H-1111 Hungary

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. © 2001 IEEE.

关键词： Visual languages

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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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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

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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