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International Joint Conference on neural Networks (IJCNN)

作者： Cs. Rekeczky G. Timar D. Balya I. Szatmari A. Zarandy AnaLogic and Neural Computing Systems Laboratory Computer Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

In this work, we present an architecture and algorithmic framework where topographic and non-topographic computation is combined on the basis of several artificial neural network models. The algorithm cores utilize an analogic (analog and logical) architecture consisting of a high resolution optical sensor, a low resolution cellular sensor-processor (cellular nonlinear network-CNN-based chip) and a digital signal processor. The proposed framework makes the acquisition of a spatially and temporally consistent image flow possible even in case of extreme variations in the environment. It ideally supports the handling of difficult problems on a moving platform such as terrain identification, navigation parameter estimation and multi-target tracking. The proposed spatio-temporal adaptation relies on a feature based optical flow estimation that can be efficiently calculated on available CNN chips. The paper illustrate how multi-channel visual flow analysis and classifier (ART, KN) driven visual attention-selection mechanisms can be efficiently supported by an analogic architecture. The experiments performed on an analogic CNN hardware prototype highlights some of the application potentials for unmanned air vehicle (UAV) applications.

关键词： neural networks computer networks Unmanned aerial vehicles Artificial neural networks computer architecture Signal processing algorithms Spatial resolution Signal resolution Optical sensors Cellular networks

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Adaptive image sensing and enhancement using the adaptive cellular neural network Universal Machine

Adaptive image sensing and enhancement using the adaptive ce...

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

作者： M. Brendel T. Roska Computer and Automation Research Institute Analogic &d Neural Computing Systems Laboratory Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

A simple but powerful active image equalization method is introduced via adaptive CNN-UM sensor-computers. The method can be used for the adaptive control of image sensing and for subsequent image enhancement. The algorithm uses intensity and contrast content as well. The method is completely executable on the adaptive cellular neural network Universal Machine (ACNN-UM) architecture. The adaptive extended cell is presented.

关键词： Adaptive systems Cellular neural networks Turing machines Image enhancement computer networks computer architecture Histograms Adaptive equalizers Adaptive control Concurrent computing

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3D integrated scalable focal-plane processor array

3D integrated scalable focal-plane processor array

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European Conference on Circuit Theory and Design, ECCTD

作者： Peter Foldesy Akos Zarandy Csaba Rekeczky Tamas Roska Analogic and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

The ASIC implementation of a 64times64 sized mixed-signal cellular visual microprocessor architecture with digital processors is described. Measurement results are shown. The architecture is composed of a regular photosensor readout circuit array, prepared for 3D sensor integration, an array of identical SIMD processing elements, and central program scheduler. The processing architecture supports cluster formation of differently parameterized arrays.

关键词： Sensor arrays Xenon computer architecture Application specific integrated circuits Processor scheduling computer interfaces Sensor phenomena and characterization Space technology Silicon Integrated circuit interconnections

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CNN Algorithms for Video Authentication and Copyright Protection

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Journal of VLSI signal processing systems for signal, image and video technology 1999年第2期23卷 449-463页

作者： Csapodi, Márton Vandewalle, Joos Preneel, Bart Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences Budapest Hungary ESAT SISTA/COSIC Laboratory Department of Electrical Engineering Katholieke Universiteit Leuven Leuven Belgium

This paper is concerned with the implementation of an image comparison algorithm and cryptographic hash functions on the regular array of cellular neural network (CNN) cells. These operations are necessary for message authentication and copyright protection in the multimedia service environment, serving both the interest of the copyright owner and the user. The basic problems of multimedia protection along with the requirements and role of the different actors in a multimedia service environment are also described here.

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Noise estimation and measures for detection of clustered microcalcifications 16th

Noise estimation and measures for detection of clustered mic...

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16th International conference on Information Processing in Medical Imaging, IPMI 1999

作者： Csapodi, Márton Petrányi, Ágota Liszka, György Zarándy, Ákos Roska, Tammás Analogic and Neural Computing Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O.B.63 BudapestH-1502 Hungary Department of Diagnostic Radiology National Institute of Oncology Kekgolyou. 13 BudapestH-1126 Hungary

ISBN: (纸本)3540661670

Image transforms used to preprocess mammogram images and highly selective microcalcification feature extraction are analyzed in this paper. It is demonstrated that the results obtained by the proposed method (especially at high true positive rates) exceed the specificity levels of other measures for which FROC analysis is provided using the same public (Nijmegen) database. © Springer-Verlag Berlin Heidelberg 1999.

关键词： Mammography

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Castle: An emulated digital CNN architecture;design issues, new results 5

Castle: An emulated digital CNN architecture;design issues, ...

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5th IEEE International Conference on Electronics, Circuits and systems, ICECS 1998

作者： Zarándy, Ákos Keresztes, Péter Roska, Tamás Szolgay, Péter Analogic and Neural Computing Systems Laboratory Computer and Automation Institute Hungarian Academy of Sciences P.O.B.63 BudapestH-1502 Hungary István Széchenyi Polytechnic Hédervári u. 3 GyôrH-9026 Hungary

ISBN: (纸本)0780350081

A new emulated digital CNN Universal Machine chip architecture is introduced in this paper. The chip contains 24 CNN core processors using 70mm2 silicon area with a 0.35 μm technology. Its speed is Ins/virtual cells/CNN iterations with 12 bits precision. This enables to execute over five hundred 3×3 convolutions on each frame of a 240×320 sized 25fps (standard NTSC) digital image flow. Another new feature of the design is the different precision capability. This allows the user to convert precision to speed. © 1998 IEEE.

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CNN based color constancy algorithm

CNN based color constancy algorithm

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

作者： L. Torok A. Zarandy Computer and Automation Reseaxh Institute Analogic and Neural Computing Laboratory Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

ISBN: (纸本)981238121X

Color constancy (CC) is a perceptional phenomena in which living species, capable of color vision, perceive object color apart from the spectral distribution of light applied to illuminate the objects. The algorithm that can recover objects' original color and display them as if they were illuminated by spectrally even (white) light is called the CC algorithm. In contrast to other solutions our approach offers on-line possibilities in applications as its operation needs consist of mainly local interactions that are well suited to the architecture of cellular neural/non-linear networks (CNN). In a recent paper, we offered a brief survey of common CC approaches, introduced the principles of our CC algorithm, compared ACE4K on-chip results versus simulation, examined the robustness of our algorithm and outlined a newly developed setup for reliable color image recording.

关键词： Cellular neural networks Lighting Robustness Color Semiconductor device modeling Humans computer vision Distributed computing Cellular networks Layout

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Trends in design of massively parallel coprocessors implemented in digital ASICs

Trends in design of massively parallel coprocessors implemen...

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International Joint Conference on neural Networks (IJCNN)

作者： P. Foldesy Analogic and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

This paper collects the most recent parallel coprocessors and highlights the recent trends. It is shown that the single chip massively parallel processor implementations seem to disappear from the scientific investigations (with the exception of low-level near-sensor image processing). Meanwhile, the formerly developed architectures have moved inside complex system-on-chips/microprocessors. The common aspect of the recent architectures is the advanced processing element and internal interconnection solutions, and the dominant mid-grain parallelism (i.e. up to a hundred processing element per chip).

关键词： Coprocessors Application specific integrated circuits Concurrent computing Parallel processing Systolic arrays Radar signal processing Signal processing algorithms Laboratories automation Image processing

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analogic Implementation of the Genetic Algorithm

Analogic Implementation of the Genetic Algorithm

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

作者： David Balya Viktor Gal Analogic and Neural Computing Systems Lab Computer and Automation Research Institute Budapest Hungary Function of Neural Circuits Laboratory Friedrich Miescher Institute for Biomedical Research Basel Switzerland

The CNN literature contains several papers about how to use the genetic algorithms for template tuning. This paper shows a possible CNN-UM implementation of the control algorithm of the genetic algorithm in a special fine-grained parallel version. The interesting of the analogic mapping is the different set of operators, which can be evaluated fast and efficient on the CNN-UM platform. The rational behind the spatial implementation is the possibility of focal-plane optimization

关键词： Genetic algorithms Biological cells Cellular neural networks Biomedical computing computer networks Evolution (biology) Algorithm design and analysis Genetic mutations Application software Application specific integrated circuits

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High-speed label inspection system for textile industry

High-speed label inspection system for textile industry

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10th IMEKO TC10 International Conference on Technical Diagnostics

作者： Szatmári, István Zarándy, Ákos Analogical and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences 13-17 Kende Street Budapest H-1111 Hungary AnaLogic Computers Ltd. 13-17 Kende Street Budapest H-1111 Hungary

ISBN: (纸本)9789638658647

In this paper, the current development of a high-speed, visual inspection unit for use in the quality assurance of narrow fabric and label weaving will be presented. The aim of the project is to provide full visual defect recognition for the textile industry. Dirt spots and patches, weaving faults, missing or torn fibers, and certain errors of the label patterns are detected. A special experimental setup was prepared for evaluating the algorithm performance. Current phase achieves a very high quality level with low false alarm rate at inspection speed of 4 m/s.

关键词： Textile industry

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