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Digital Information processing and Communications, Part ii 2011

丛书名： Communications in Computer and Information Science

2011年

作者： Vaclav Snasael Jan Platos Eyas El-Qawasmeh

ISBN: (数字)9783642224102

ISBN: (纸本)9783642224096

This two-volume-set (CCIS 188 and CCIS 189) constitutes the refereed proceedings of the International Conference on Digital Information processing and Communications, ICDIPC 2011, held in Ostrava, Czech Republic, in July 2011. The 91 revised full papers of both volumes presented together with 4 invited talks were carefully reviewed and selected from 235 submissions. The papers are organized in topical sections on network security; Web applications; data mining; neural networks; distributed and parallel processing; biometrics technologies; e-learning; information ethics; image processing; information and data management; software engineering; data compression; networks; computer security; hardware and systems; multimedia; ad hoc network; artificial intelligence; signal processing; cloud computing; forensics; security; software and systems; mobile networking; and some miscellaneous topics in digital information and communications.

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Intelligent vision system for quality classification of airport lamp prisms 25

Intelligent vision system for quality classification of airp...

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25th IEEE Conference on Signal processing - Algorithms, Architectures, Arrangements, and applications (IEEE SPA)

作者： Suder, Jakub Podbucki, Kacper Marciniak, Tomasz Dabrowski, Adam Poznan Univ Tech Fac Automat Control Robot & Elect Engn Inst Automat Control & Robot Div Elect Syst & Signal Proc Jana Pawla II 24 PL-60965 Poznan Poland

ISBN: (数字)9788362065424

ISBN: (纸本)9788362065424

The article presents a concept of the analysis of mechanical wear of prisms in the in-pavement airport lamps. The solution is based on image processing technique that requires an appropriate selection of parameters due to the specificity of the objects. During the experimental tests, a database consisting of 316 photos of IDM airport lamps mounted in the airport areas was used. The proposed solution using an artificial neural network allows for the classification of lamps with an efficiency of 81.4%.

关键词： system airport lighting control neural networks artificial intelligence Hough transform

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Target detection using multilayer feedforward neural networks

Target detection using multilayer feedforward neural network...

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applications of artificial neural networks ii

作者： Scherf, Alan V. Scott, Peter A. Loral Aeronutronic Newport Beach CA USA

ISBN: (纸本)0819405787

Multilayer feedforward neural networks have been integrated with conventional image processing techniques to form a hybrid target detection algorithm for use in the F/A-18 FLIR pod advanced air-to-air track-while-scan mode. The network has been trained to detect and localize small targets in infrared imagery. Comparative performance between this target detection technique is evaluated.

关键词： Computer Vision

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Classification of Cervical Cancer using artificial neural networks 12

Classification of Cervical Cancer using Artificial Neural Ne...

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12th International Conference on Communication networks (ICCN) / 12th International Conference on Data Mining and Warehousing (ICDMW) / 12th International Conference on image and Signal processing (ICISP)

作者： Devi, M. Anousouya Ravi, S. Vaishnavi, J. Punitha, S. Pondicherry Univ Sch Engn & Technol Pondicherry India

artificial neural network (ANN) plays an important role in many medical imaging applications. The detection of cervical cancer cells uses an ANN for classifying the normal and abnormal cells in the cervix region of the uterus. Cervical cancer detection is very challenging because this cancer occurs without any symptoms. The classification between the normal, abnormal and cancerous cells is identified by using an artificial neural network which produces accurate results than the manual screening methods like Pap smear and Liquid cytology based (LCB) test. The ANN uses several architectures for easy and accurate detection of cervical cells. In this paper, a survey and analysis on the different types of architecture in the ANN with its accuracy results and performance are discussed. A brief description about the working and detection of cervical cancer is presented which is useful for the classification of normal and abnormal cervical cells. (C) 2016 The Authors. Published by Elsevier B.V.

关键词： artificial neural Network (ANN) Cervical Cancer Liquid Cytology Based Test (LCB) Pap Smear Test

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Invariant pattern recognition via higher order preprocessing and backprop

Invariant pattern recognition via higher order preprocessing...

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applications of artificial neural networks ii

作者： Davis, Jon P. Schmidt, William A. Naval Air Development Cent. Warminster PA USA

ISBN: (纸本)0819405787

Higher-order neural networks are a variation of the standard back-propagation neural network, using geometrically motivated nonlinear combinations of scene pixel values as a feature space. The effects of varying feature size (in number of pixels), scene size, number of features, summation-over-scene versus maximum-over-scene, and number of hidden layers, are examined.

关键词： image processing

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Analysis and improvement of neural network robustness for on-board satellite image processing 7th

Analysis and improvement of neural network robustness for on...

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7th International Conference on artificial neural networks, ICANN 1997

作者： Muller, J.-D. Cheynet, P. Velazco, R. Commissariat à l'Energie Atomique CEA/DAM/DRIF DCRE/EIM B.P Bruyères-le-Châtel12-91680 France Institut de Mathématiques Appliquées de Grenoble IMAG/LSR 46 avenue Félix Viallet Grenoble Cedex38031 France

ISBN: (纸本)3540636315

The topic of this work, a joint scientific program merging the CEA, the IMAG, the CNES (France) and the Naval Research Laboratories (USA), is the evaluation of connectionist techniques for on-board signal and image processing applications in radiative environments (e.g.: space). The objective is to define methods which improve the robustness with respect to radiations of electronic neural systems applied to artificial perception. Theoretical and simulation results are compared to two kinds of experiments: ground tests, performed in France and in the United States on electronic components and boards, ® an experiment on a neural artificial vision application embedded in a satellite (launch expected in July 1997). In this paper, we describe the first results of our work: after having verified on a natural texture classification application that training a neural network in noisy conditions leads to a significant improvement of robustness, we propose an interpretation of this phenomenon and suggest the use of simple activation functions, compatible with robustness. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Research laboratories

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Electrogram analysis during atrial fibrillation using wavelet and neural network techniques

Electrogram analysis during atrial fibrillation using wavele...

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Conference on Wavelet applications in Signal and image processing V

作者： Govindan, A Deng, G Power, J La Trobe Univ. (Australia) Austin Hospital (Australia)

ISBN: (纸本)0819425915

Atrial fibrillation (AF) is a common arrhythmia associated with many heart diseases and has a high rate of incidence in the older population. Many of the symptoms of AF are poorly tolerated by patients and if not properly managed, may lead to fatal conditions like embolic stroke. The atrial electrograms during AF show a high degree of non-stationarity AF being progressive in nature, we aim to link the the degree of non-stationarity of the atrial electrogram to the stage of advancement of the disease, the duration of episodes of AF, possibility of spontaneous reversion to sinus rhythm and the defibrillation energy requirement. In this paper we describe a novel algorithm for classifying bipolar electrograms from the right atrium of sheep into four groups - normal sinus rhythm, atrial flutter, paroxysmal AF, chronic AF. This algorithm uses features derived from a wavelet transform representation of the signal to train an artificial neural network which is then used to classify the different arrhythmia. The success rates achieved for each subclass indicates that this approach is well suited for the study of atrial arrhythmia.

关键词： wavelet transform artificial neural networks pattern recognition atrial fibrillation kurtosis non-stationary signal analysis

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New improved feature extraction methods for real-time high performance image sequence recognition

New improved feature extraction methods for real-time high p...

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1997 IEEE International Conference on Acoustics, Speech, and Signal processing (ICASSP 97)

作者： Rigoll, G Kosmala, A Gerhard-Mercator-Univ Duisburg Duisburg Germany

ISBN: (纸本)0818679204

This paper describes new feature extraction methods which can be used very effectively in combination with statistical methods for image sequence recognition. Although these feature extraction methods can be used for a wide variety of image sequence processing applications, the target application presented in this paper is gesture recognition. The novel feature extraction methods have been integrated into an HMM-based gesture recognition system and led to substantial improvements for this system. It turned out that the new features are not only able to describe the gesture characteristics much better than the old features, but additionally they also led to a dramatic reduction in dimensionality of the feature vector used for representing each frame of the image sequence. This resulted in the fact that it was possible to use the novel features in Combination with a new architecture for statistical image sequence recognition. The result of this investigation is a high performance gesture recognition system with significantly improved recognition rates and real-time capabilities.

关键词： Feature extraction

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artificial neural NETWORK MODELS FOR image UNDERSTANDING 2

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CONF ON image processing ALGORITHMS AND TECHNIQUES

作者： KULKARNI, AD BYARS, P Univ. of Texas/Tyler (United States)

ISBN: (纸本)0819405515

In this paper we introduce a new class of artificial neural network (ANN) models based on transformed domain feature extraction. Many optical and/or digital recognition systems based on transformed domain feature extraction are available in practice. Optical systems are inherently parallel in nature and are preferred for real time applications, whereas digital systems are more suitable for nonlinear operations. In our ANN models we combine advantages of both digital and optical systems. Many transformed domain feature extraction techniques have been developed during the last three decades. They include: the Fourier transform (FT), the Walsh Hadamard transform (WHT), the discrete cosine transform (DCT), etc. As an example, we have developed ANN models using the FT and WHT domain features. The models consist of two stages, the feature extraction stage and the recognition stage. We have used back-propagation and competitive learning algorithms in the recognition stage. We have used these ANN models for invariant object recognition. The models have been used successfully to recognize various types of aircraft, and also have been tested with test patterns. ANN models based on other transforms can be developed in a similar fashion.

关键词： Feature extraction Fourier transforms Sensors image processing Electro optical modeling Detection and tracking algorithms Francium Matrices Systems modeling artificial neural networks

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A prototype for Brazilian bankcheck recognition

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND artificial INTELLIGENCE 1997年第4期11卷 549-569页

作者： Lee, LL Lizarraga, MG Gomes, NR Koerich, AL UNIV ESTADUAL CAMPINAS UNICAMPFEECDECOMBR-13081970 CAMPINASSPBRAZIL

This paper describes a prototype for Brazilian bankcheck recognition. The description is divided into three topics: bankcheck information extraction, digit amount recognition and signature verification. In bankcheck information extraction, our algorithms provide signature and digit amount images free of background patterns and bankcheck printed information. In digit amount recognition, we dealt with the digit amount segmentation and implementation of a complete numeral character recognition system involving image processing, feature extraction and neural classification. In signature verification, we designed and implemented a static signature verification system suitable for banking and commercial applications. Our signature verification algorithm is capable of detecting both simple, random and skilled forgeries. The proposed automatic bankcheck recognition prototype was intensively tested by real bankcheck data as well as simulated data providing the following performance results: for skilled forgeries, 4.7% equal error rate;for random forgeries, zero Type I error and 7.3% Type ii error;for bankcheck numerals, 92.7% correct recognition rate.

关键词： bankcheck recognition signature verification numeral character recognition image processing

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