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ACORNS - towards computational modeling of communication and recognition skills

ACORNS - towards computational modeling of communication and...

引用

IEEE international conference on Cognitive Informatics

作者： Lou Boves Louis ten Bosch Roger Moore Department Language and Speech Radboud University Nijmegen Netherlands Department of Computer Science University of Sheffield UK

In this paper the FP6 Future and Emerging Technologies project ACORNS is introduced. this project aims at simulating embodied language learning, inspired by the memory-prediction theory of intelligence. ACORNS intends to build a full computational implementation of sensory information processing. ACORNS considers linguistic units as emergent patterns. thus, the research will not only address the issues conventionally investigated in statistical pattern recognition, but also the representations that are formed in memory. the paper discusses details of the memory and processing architecture that will be implemented in ACORNS, and explains how this architecture merges the basic concepts of the Memory-Prediction theory with results form previous research in the field of memory.

关键词： Computational modeling Automatic speech recognition pattern recognition Speech recognition Humans Speech processing Natural languages Memory architecture Machine learning Training data

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Nonstationary power signal processing and pattern recognition using genetic algorithm

Nonstationary power signal processing and pattern recognitio...

引用

international conference on Information, Communications and Signal Processing

作者： B. Biswal T. K Panda S Hasan P.K. Dash B .K Panigrahi Electronics Department Silicon Institute of Technology India ITER Deemed University India IIT New Delhi India

ISBN: (纸本)9781424409822

A new approach to time frequency transform and pattern recognition of non-Stationary power signals is presented in this paper. In the proposed work Visual localization, detection and classification of non-stationary power signals are achieved using HS-Transform and automatic pattern recognition is carried out using fuzzy C-means based Genetic algorithm. Time frequency analysis and Feature extraction from the non- stationary power signals is done by HS-Transform. Once the feature vectors are extracted is used for pattern recognition of various non-Stationary signals. Various non-stationary power signals are processed through HS-transform with hyperbolic window to generate time-frequency contours for extracting relevant features for pattern classification. the extracted features are clustered using fuzzy C-means algorithm and finally the algorithm is extended using Genetic algorithm to refine the cluster centers. the average classification accuracy of the disturbances is 93.25% and 95% using fuzzy C-means and Genetic based fuzzy C-means algorithm, respectively.

关键词： Signal processing algorithms pattern recognition Genetic algorithms Feature extraction Time frequency analysis Clustering algorithms Signal processing Power generation Signal generators pattern classification

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Architecture of Transform Based Invariant Feature Memory

Architecture of Transform Based Invariant Feature Memory

引用

international conference on Systems, Signals and Image Processing, IWSSIP

作者： J. Turan L'. Ovsenik Department of Electronics and Multimedia Communications University of Technology Ko¡ice Ko¡ice Slovak Republic

Presented paper deals with the problem of design transform based invariant associative image memory. Invariant feature selection is solved using the Trace transform and the Karhunen -Loeve transform (TT-KLT). System p... 详细信息

关键词： Karhunen-Loeve transforms Feature extraction Decorrelation Image recognition Image coding pattern recognition Associative memory Image segmentation Filtering Computer architecture

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Radial Krawtchouk moments for rotational invariant pattern recognition

Radial Krawtchouk moments for rotational invariant pattern r...

引用

international conference on Information, Communications and Signal Processing

作者： P. Ananth raj A. Venkataramana Department of Electronics and Communication College of Engineering Osmania University Hyderabad Andhra Pradesh India Department of Electronics and Communication Engineering Government Polytechnic College Mahabubnagar Andhra Pradesh India

ISBN: (纸本)9781424409822;1424409829

Krawtchouk moments are not rotational invariant. Hence, this paper introduces a new radial Krawtchouk moments using polar representation of an image by a one dimensional orthogonal discrete weighted Krawtchouk polynomials and a circular function. Further rotational invariants are derived from the proposed radial Krawtchouk moments. In order to test the proposed approach, three problems namely image reconstruction, rotational invariance and texture recognition are attempted using the proposed moments. In order to assess the quality of the reconstructed image, reconstruction error, peak signal to noise ratio (PSNR) and universal image quality index (UIQI) are computed. It is observed from the simulation results that the reconstructed image converges to the original image as the order of the moments is increased. Further more, the difference in rotational invariants before and after the rotation of an image is very small. Finally, the test texture images are correctly recognized from a set of texture images that are available in a small database.

关键词： pattern recognition Image reconstruction Testing Image recognition PSNR Polynomials Image quality Computational modeling Image converters Image databases

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A tongue-print image database for recognition

A tongue-print image database for recognition

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6th international conference on Machine Learning and Cybernetics

作者： Liu, Zhi Yan, Jing-Qi Zhang, David Tang, Qun-Lin Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200030 Peoples R China Hong Kong Polytech Univ Biometr Res Ctr Dept Comp Kowloon Peoples R China Grad Sch Harbin Inst Technol Shenzhen Peoples R China

ISBN: (纸本)9781424409723

the tongue is a unique organ in that it can be stuck out of mouth for inspection, in this act offering a proof of life, and yet it is otherwise well protected in the mouth and is difficult to forge. the tongue also presents both geometric shape information and physiological texture information which are potentially useful in identity verification applications. Furthermore, the act of physically reaching or thrusting out is a convincing proof for the liveness. Despite these obvious advantages, little work has hitherto been done on tongue features. A primary factor for preventing such research is the lack of an available 3D tongue image database. In this paper, we present a newly developed 3D tongue image database, which includes. both tongue geometric shape and surface textures of 134 subjects. this is the first attempt at making a 3D tongue image database available for the research community, with the ultimate goal of fostering;the research on tongue biometrics. the new database can be a valuable resource for algorithm assessment, comparison and evaluation.

关键词： tongue-prints database biometrics verification

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A Study on the Importance of Biometric Technique Selection in the Protection of Company Resources

A Study on the Importance of Biometric Technique Selection i...

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Computer Information Systems and Industrial Management Applications (CISIM)

作者： Anna Zajkowska Wojciech Zimnoch Khalid Saeed Faculty of Management Bialystok Technical University Bialystok Poland Faculty of Computer Science Bialystok Technical University Bialystok Poland

In this paper some modern methods of physiological identification of people, the importance of biometrics in company management, and technical resources used in this field are presented. Authors describe the achievements of biometrics and its efficiency in ensuring the security of data and equipment resources from industrial management point of view. Also given the advantages of the solutions that are based on biometric methods, and evidence showing their increasing significance in company activity and its development.

关键词： Biometrics Protection Fingerprint recognition Face recognition pattern recognition Resource management Data security Application software Shape measurement Humans

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A fully Automated CAD system using Multi-category Feature Selection with Restricted Recombination

A fully Automated CAD system using Multi-category Feature Se...

引用

international conference on Computer and Information Science (ACIS)

作者： Ranadhir Ghosh Moumita Ghosh John Yearwood Subhasis Mukherjee University of Ballarat Australia

In pattern recognition problems features plays an important role for classification results. It is very important which features are used and how many features are used for the classification process. Most of the real life classification problem uses different category of features. It is desirable to find the optimal combination of features that improves the performance of the classifier. there exists different selection framework that selects the features. Mostly do not incorporate the impact of one category of features on another. Even if they incorporate, they produce conflict between the categories. In this paper we proposed a restricted crossover selection framework which incorporate the impact of different categories on each other, as well as it restricts the search within the category which searching in the global region of the search space. the results obtained by the proposed framework are promising.

关键词： pattern recognition Biological cells Search engines Cancer Biomedical imaging Medical diagnostic imaging Computer network reliability Image analysis Digital images Image processing

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LDA enhanced moments

LDA enhanced moments

引用

international conference on Information, Communications and Signal Processing

作者： Pew-thian Yap Xudong Jiang Alex Chichung Kot School of Electrical & Electronic Engineering (EEE) Nanyang Technological University Singapore

ISBN: (纸本)9781424409822;1424409829

Moments and functions of moments are powerful tools in a vast number of fields, particularly image signal processing. In this paper, a method for obtaining a set of orthogonal, noise-robust, and distribution-adaptive moments, called Fishermoments (FM), is presented. FM are obtained by performing linear discriminant analysis (LDA) in the moment space resided by geometric moments (GM). the moment space is transformed into the feature space where a separability criterion is maximized. Experiments performed to gauge the performance of FM show significant improvements in terms of accuracy and noise robustness as predicted by the theoretical framework.

关键词： Linear discriminant analysis Kernel Eigenvalues and eigenfunctions Decorrelation Noise robustness Image analysis Polynomials Power engineering and energy Multidimensional signal processing pattern recognition

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Highly Compressed Zernike Moments by Smoothing

Highly Compressed Zernike Moments by Smoothing

引用

international conference on Systems, Signals and Image Processing, IWSSIP

作者： G. A. Papakostas Y. S. Boutalis D. A. Karras B. G. Mertzios Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Automation Chalkis Institute of Technology Chalkida Greece Department of Automation Laboratory of Control Systems. and Computer Intell. Thessaloniki Institute of Technology Thessaloniki Greece

A novel methodology that improves the discrimination capabilities of the compressed feature vectors, used in pattern recognition tasks, is presented in this paper. the Zernike moment signals of some patterns are extracted and are compressed by using a typical wavelet compression technique. In order to increase the compression ratio without loosing a great amount of significant information, the moment signals are smoothed appropriately before the compression. As a result, highly compressed feature vectors that include enough classification information are derived. the resulted improved features are studied for their discriminative power through appropriate experiments.

关键词： Smoothing methods Image coding Polynomials Automation Feature extraction pattern classification Digital images Image reconstruction Laboratories Automatic control

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Semantic knowledge in williams syndrome: Insights from comparing behavioural and brain processes in false memory tasks

Semantic knowledge in williams syndrome: Insights from compa...

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IEEE international conference on Development and Learning, ICDL

作者： Ching-Fen Hsu Annette Karmiloff-Smith Ovid Tzeng Rung-Tai Chin Hua-Chen Wang Centre for Brain and Cognitive Development Birkbeck University of London UK Centre for Brain and Cognitive Development Birkbeck University of London UK Laboratory for Cognitive Neuroscience National Yang-Ming University Taiwan Laboratory for Cognitive Neuroscience National Yang Ming University Taiwan Department of Linguistics University of Postdam Germany

this study attempts to understand the relationship between use of context and semantic knowledge in the genetic disorder, Williams syndrome (WS).Earlier work had arrived at discrepant results, suggesting either near normal semantic priming [10), or unusual lexical organization [5] and atypical sentence integration [8] in this clinical group. To address these discrepant findings, we used two methodologies with an auditory false memory paradigm, and measured behavioural and neurophysiological (ERP) responses from three groups: children and adults with WS, Mental-Age matched normal children, and normal adults. While the behavioural data suggested that individuals with WS revealed a similar pattern of recognition as both groups of controls for words with semantic relatedness, their neurophysiological correlates suggested a different pattern. Our findings indicate that WS proficient compensatory behaviour camouflages a deviant neural pathway in the use of contextual cues. Our results also point to neurological changes during typical development, since typically developing children showed a distinctive pattern from our adult participants. Overall, our findings suggest that semantic organization develops slowly over typical development, and atypically in the Williams syndrome.

关键词： Testing Delay Laboratories Neuroscience Genetics Enterprise resource planning pattern recognition Neural pathways Autism Recruitment

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