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检索条件"机构=AnaLogic and Neural Computing Systems Laboratory Computer Automation Research Institute"

共 149 条记录，以下是61-70 订阅

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High-speed label inspection system for textile industry

High-speed label inspection system for textile industry

引用

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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Neuromorphic algorithm for retinal implants

Neuromorphic algorithm for retinal implants

引用

International IEEE/EMBS Conference on neural Engineering, CNE

作者： D. Balya B. Roska Analogic and Neural Computing Laboratory Computer and Automation Research Institute Budapest Hungary Harvard Society of Fellows Harvard University Cambridge MA USA

The paper focuses on the input transformation for retinal implants. It describes a novel retina model, based on neurobiological measurements. Our modeling approach is neuromorphic, however the primary motivation is to derive an algorithmic skeleton from the animal retina measurements. The on-line, real-time implementation of the algorithm is given for an off-the-shelf stand-alone system, called Bi-I

关键词： Neuromorphics Retina Cochlear implants Optical transmitters Neurons Ear Biomedical acoustics Image restoration Signal restoration Stimulated emission

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Seismic wave propagation modelling on emulated digital CNN-UM architecture

Seismic wave propagation modelling on emulated digital CNN-U...

引用

作者： Kozma, Péter Nagy, Zoltán Szolgay, Péter Department of Image Processing and Neurocomputing University of Veszprém Egyetem u. 10 H-8200 Veszprém Hungary Analogic and Neural Computing Laboratory Computer and Automation Institute HAS Kende u. 13-17 H-1111 Budapest Hungary

The synthetic seismogram has seen many years of widespread and successful application in geophysical prospecting. It is used to simulate the normal incidence reflectivity of a horizontally stratified medium and has been employed more recently to obtain the responses of subsurface structural and stratigraphie configurations. The solution of the partial differential equations of motion describing the propagation of stress waves in an elastic medium requires enormous computation power. In this paper a solution of seismic wave propagation will be presented on CNN-UM architecture. Unfortunately the space-dependent equations and the low computational precision do not make it possible to utilize the huge computing power of the analog CNN-UM chips so the Falcon emulated digital CNN-UM architecture is used to improve the performance of our solution.

关键词： Electromagnetic wave propagation

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Elastic wave propagation modeling on emulated digital CNN-UM architecture

Elastic wave propagation modeling on emulated digital CNN-UM...

引用

9th IEEE International Workshop on Cellular neural Networks and their Applications, CNNA

作者： Kozma, Péter Sonkoly, Péter Szolgay, Péter Department of Image Processing and Neurocomputing University of Veszprém Egyetem u. 10 H-8200 Veszprém Hungary Department of Image Processing and Neurocomputing University of Veszprém Analogic and Neural Computing Laboratory Computer and Automation Institute HAS Kende u. 13-17 H-1111 Budapest Hungary

The synthetic seismogram has seen many years of widespread and successful application in geophysical prospecting. It is used to simulate the normal incidence reflectivity of a heterogeneous medium and has been employed more recently to obtain the responses of subsurface structural and stratigraphic configurations. The propagation of seismic waves has to be modeled to create synthetic seismograms. The solution of the partial differential equations of motion describing the propagation of stress waves in an elastic medium requires enormous computation power. In this paper a solution of seismic wave propagation will be presented on CNN-UM architecture. Unfortunately the space-dependent equations and the low computational precision do not make it possible to utilize the huge computing power of the analog CNN-UM chips so the Falcon emulated digital CNN-UM architecture is used to implement our solution.

关键词： Cellular neural networks

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A new CNN template for POAC peak enhancement

A new CNN template for POAC peak enhancement

引用

European Conference on Circuit Theory and Design, ECCTD

作者： A. Ayoub S. Tokes Analogic and Neural Computing Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary Magyar Tudomanyos Akademia Szamitastechnikai es Automatizalasi Kutatointezet Budapest Budapest HU

We propose a CNN template to enhance the POAC output (correlogram peaks) for higher detection accuracy. Our recursive algorithm found the optimum template values under the one-third condition. The statistical, simulation and practical results confirmed that the template: enhances the correlogram peaks' detection; is fast for real time applications; is suitable to work under several illuminations; and avoids the complexity of adaptive thresholding.

关键词： Cellular neural networks Band pass filters Optical feedback Equations Lighting Optical computing Optical filters Computational modeling Adaptive optics Optical fiber networks

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Elastic wave propagation modeling on emulated digital CNN-UM architecture

Elastic wave propagation modeling on emulated digital CNN-UM...

引用

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

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

The synthetic seismogram has seen many years of widespread and successful application in geophysical prospecting. It is used to simulate the normal incidence reflectivity of a heterogeneous medium and has been employed more recently to obtain the responses of subsurface structural and stratigraphic configurations. The propagation of seismic waves has to be modeled to create synthetic seismograms. The solution of the partial differential equations of motion describing the propagation of stress waves in an elastic medium requires enormous computation power. In this paper a solution of seismic wave propagation will be presented on CNN-UM architecture. Unfortunately the space-dependent equations and the low computational precision do not make it possible to utilize the huge computing power of the analog CNN-UM chips so the Falcon emulated digital CNN-UM architecture is used to implement our solution.

关键词： Partial differential equations computer architecture Cellular neural networks Geophysics computing Seismic waves Stress Analog computers Image processing Very large scale integration Numerical models

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Efficient off-line feature selection strategies for on-line classifier systems

Efficient off-line feature selection strategies for on-line ...

引用

International Joint Conference on neural Networks (IJCNN)

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

In this work we discuss feature/signature selection strategies for on-line classifier systems, implemented on a common stand-alone HW/SW vision system. In the chosen computational environment topographic and non-topographic computing can be combined for the targeted task of terrain feature analysis. The topographic front-end of the system is capable of deriving more than thousand different visual signatures per second from a few dozen visual feature channels. These signatures are statistically correlated and might also be computationally inter-dependent. To develop an efficient real-time classification algorithm the dimensionality of the extracted features has to be significantly reduced, i.e. only a few signatures can be selected. In this paper we analyze different signature selection strategies for various classifiers with given performance criteria and system-level time performance constraints. Two blind signature selection techniques are described: variance maximization and a factor-based analysis. We also discuss supervised selection mechanisms: class-based statistical and decision-tree-based approaches.

关键词： Feature extraction computer vision Classification algorithms Performance analysis Hardware Microprocessors Laboratories automation Machine vision Time factors

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Topographic and non-topographic neural network based computational platform for UAV applications

Topographic and non-topographic neural network based computa...

引用

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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Trends in design of massively parallel coprocessors implemented in digital ASICs

Trends in design of massively parallel coprocessors implemen...

引用

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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Hand gesture recognition in camera-projector system

引用

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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