Revisão Bibliográfica: Learning Vector Quantization 28/04/2003



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Median Radial Basis Functions Network for Optical Flow Processing - Bors, Pitas  
layer weights are estimated based on Learning Vector Quantization (LVQ)In the second stage the out-
www-users.cs.york.ac.uk/~adrian/HTML/../Papers/Conferences/NSIP95.pdf

Optical Flow Estimation and Moving Object Segmentation Based on .. - Bors, Pitas  
a clustering approach, similar to the Learning Vector Quantization (LVQ) 28]A robust statistics-based
poseidon.csd.auth.gr/papers/PUBLISHED/JOURNAL/Bors98a/Bors97d.ps.Z


    • Object Localization in 2D Images based on Kohonen's.. - Yuan, Niemann (1999)  
      network trained with dynamic learning vector quantization (DLVQ)By using a hidden layer
      www5.informatik.uni-erlangen.de/literature/ps-dir/1999/Yuan99:IJCNN.ps.gz
      Abstract: This paper presents a hybrid approach for neural object localization and recognition in 2D grey level images. The system combines an auto-associative network, two self-organization feature maps (SOMs), and a three layer feed-forward network trained with dynamic learning vector quantization (DLVQ). By using a hidden layer smaller than the input/output layers, the auto-associative network can be expected to find efficient ways of encoding the information contained in the input data set. Thus a...



  • Artigos Similares:


Image Segmentation Based on a Dynamically Coupled Neural.. - Chen, Wang  
Range Image Segmentation Using a Relaxation Oscillator Network - Liu, Wang (1999)  
Nonlinear Features for Classification and Pose Estimation.. - Talukder, Casasent (1998)  

Detection of Spectra in Objective Prism Images Using Neural.. - Smareglia, Pasian  
Analysis of Autoassociative Mapping Neural Networks - Ikbal, Misra, Yegnanarayana (1999)  
Recurrent Autoassociative Networks - Developing Distributed.. - Stoianov  


  • Citações:


The self-organizing map - Kohonen - 1990
Lvq pak: the learning vector quantization program package - Kohonen, Hynninen et al. - 1996
Berlin-Heidelberg-New YorkTokio - Kohonen, Associative et al. - 1989
Recognition and pose estimation of unoccluded three-dimensio.. - Khotanzad - 1996
Multiscale image segmentation using a hierarchical self-orga.. - Bhandarkar, Koh et al. - 1997
Object Recognition from 2D images using Kohonen Self-Organis.. - Lakany, Schukat-Talamazzini et al. - 1997
An extended Kohonen phonetic map - Albeverio, Kruger et al. - 1997
Globally Optimal Vector Quantizer Design Using Stochasticall.. - Bi, Bi et al. - 1994
Bonn-Paris-New York-Tokyo-Singapore - Zell, Netze - 1994
Studies on object recognition from degraded images using neu.. - Ravichandran, Yegnanarayana - 1995



  • Site: http://www5.informatik.uni-erlangen.de/literature/English/Alles/Alles.html



Duration Features in Prosodic Classification: Why.. - Batliner, Nöth.. (2001)  
Using Prosodic Features To Characterize Off-Talk In.. - Siepmann, Batliner.. (2001)  
3-D Reconstruction and Camera Calibration from Images with.. - Socher, Merz, Posch (1995)  


    • LANDSAT - TM Image Classification Using Principal.. - Sergi Solaiman And  
      Feature Map (SOFM)the Hybrid Learning Vector Quantization (HLVQ) and the Multi Layer Perceptron
      perso-iti.enst-bretagne.fr/~solaiman/Documents/Publis/Pdf/IGARSS.pdf
      Abstract: this paper , the application of neural networks for multispectral images analysis is discussed. Data analysis methods for remotely sensed images are mainly based on statistical approaches, such as maximum likelihood or Bayesian mathods. In this case, classification is performed under Gaussian assumption. But, recent papers concerning the application of neural networks to remotely sensed data classification, prove that neural networks provide an intersting alternative to statistical methods...



  • Artigos Similares:


A comparative study on multispectral agricultural images.. - Solaiman Mouchot Brown  
Medical Image Compression and Feature Extraction using.. - Guy Cazuguel Andras  
A Comparative Study of Conventional and Neural Network.. - Multispectral Data..  
Multispectral LANDSAT Images Segmentation using Neural.. - Solaiman, Mouchot, Koffi  
Multisensor data fusion using fuzzy concepts: Application .. - Solaiman, Pierce, Ulaby (1999)  
Multisensor fusion through fuzzy reasoning. Application .. - Solaiman Pierce..  


  • Citações:


Introduction to the Theory of Neural Computation - Hertz, Krogh et al. - 1991
Self-Organization and Associative Memory - Kohonen - 1989   Book Details from Barnes & Noble  
Multispectral Classification of Landsat-Images Using Neural .. - Bischof, Schneider et al. - 1992
Neural Network Approaches Versus Statistical Methods in Clas.. - Benediktsson, Swain et al. - 1990
A Hybrid Algorithm, HLVQ, Combining Unsupervised and Supervi.. - Solaiman, Mouchot et al. - 1994
A Comparative Study of Conventional and Neural Network Class.. - Solaiman, Mouchot – 1994


  • Site: http://perso-iti.enst-bretagne.fr/~solaiman/Publi.html



Multisensor fusion through fuzzy reasoning. Application .. - Solaiman Pierce..  
Multisensor data fusion using fuzzy concepts: Application .. - Solaiman, Pierce, Ulaby (1999)  
A comparative study on multispectral agricultural images.. - Solaiman Mouchot Brown  

Image Analysis For Material Characterisation - Livens (1998)  



  • Site: wcc.ruca.ua.ac.be/~livens/phd1.ps.gz



  • Artigos Similares:

 
Image Analysis For Material Characterisation - Livens  
A Texture Analysis Approach to Corrosion Image.. - Livens, Scheunders.. (1996)  

Wavelet-based Texture Analysis - Scheunders, Livens, Wouwer, Vautrot, .. (1997)  
An Adaptive Texture and Shape Based Defect Classification - Iivarinen, Visa (1998)  
Wavelets as chromatin texture descriptors for the.. - Wouwer, Weyn.. (2000)  
Wavelets For Multiscale Texture Analysis - Wouwer (1998)  
Reader CKI-10 2001 / 2002 - Samenstelling Maarten Janssen  
Computer Algebra Nederland Nieuwsbrief 5 - Juni Inhoud Inleiding  


  • Citações:


Self-organizing Maps - Kohonen - 1995   Book Details from Amazon or Barnes & Noble  
Orthonormal bases of compactly supported wavelets - Daubechies - 1988
Symmetric phase only matched filtering of fourier mellin tra.. - Chen, Defrise et al. - 1994
LVQ PAK: The Learning Vector Quantization program package - Kohonen, Hynninen et al. - 1996
LVQ classification of corrosion images from wavelet represen.. - Livens, Scheunders et al. - 1995
Texture defect detection: a review - Song, Petrou et al. - 1992
LVQ classification of corrosion images from wavelet represen.. - Livens, Scheunders et al. - 1995
LVQ classification of corrosion images from wavelet features - Livens, Scheunders et al. - 1995
A texture analysis approach to corrosion image classificatio.. - Livens, Scheunders et al. - 1996
A texture analysis approach to corrosion image classificatio.. - Livens, Scheunders et al. - 1996
Wavelets for texture analysis - Livens - 1997
Wavelet correlation signatures for color texture characteriz.. - Wouwer, Livens et al. - 1997
Colour image analysis for light microscopy - Livens - 1996
Deriving corrosion knowledge from case histories: the neural.. - Smets, Bogaerts - 1992
Wavelets for texture analysis: an overview - Livens, Wouwer - 1997
Circular-mellin features for texture segmentation - Ravichandran, Trivedi - 1995
Designing a defect classification system: A case study - Brzakovic, Vujovic - 1996
Karakterisatie van corrosiebeelden - Livens - 1994
Karakterisatie van corrosiebeelden - Livens - 1994
Rotation-invariant texture segmentation using continuous wav.. - Wouwer, Vautrot et al. - 1997
Computer aided corrosion engineering - Bogaerts, Smets et al. - 1993
Colour texture classification by wavelet energy-correlation .. - Wouwer, Livens et al. - 1997
Special issue on Image Processing - Scheunders, Livens et al. - 1998
Towards rotational invariant wavelet features for texture an.. - Livens - 1996
Texture analysis using wavelet features; an application in c.. - Livens, Scheunders et al. - 1996
Continuous wavlets for rotation-invariant texture classifica.. - Vautrot, Wouwer et al. - 1997
How to measure the shape of silver halide microcrystals - Livens - 1997
A new approach towards self adaptive object recognition - Van Dyck, Livens et al. - 1994
an ideal tool for multiscale image analysis - Livens, Wouwer - 1996
A Connectionist System for Corrosion Failure Analysis and Ri.. - Smets - 1995
Measuring small objects from digital images : what limits th.. - Livens - 1998
Granulometric segmentation using a gradient convergence map - Livens, Van Roost et al. - 1997
On optimal image quantizers and their dependence on initial .. - Scheunders, Van Hove et al. - 1995
Automatic casting surface defect recognition and classificat.. - Wong, Elliot et al. - 1995
Pipe corrosion inspection crawler fact sheet - Marsh - 1996
The era of corrosion automata - a retrospect of corrosion - Bogaerts


  • Site: Citeseer.nj.nec.com


Object Segmentation in 3-D Images Based on Alpha-Trimmed Mean.. - Bors, Pitas  
In the classical approach based on the Learning Vector Quantization, the center is updated using: i (X -
www-users.cs.york.ac.uk/~adrian/HTML/../Papers/Conferences/EUS98a.pdf

Fast Image Analysis Using Kohonen Maps - Willett Busch (1994)     (1 citation)
additional postprocessing with learning vector quantization (LVQ) is recommended [7]3 SPEED-UP
www.fb9-ti.uni-duisburg.de/mitarbeiter/willett/ieee94_e.ps.gz

Image annotation based on Learning Vector Quantization and.. - Blume, Ballard (1997)     (3 citations)
Page 1 Image annotation based on Learning Vector Quantization and localized Haar wavelet transform
www.reticular.com/Library/ImageAnnot/aerosens.ps

Region-Based Relevance Feedback In Image Retrieval - Jing, Li, Zhang, Zhang (2002)  
of the retrieved images. Then the Learning Vector Quantization (LVQ) algorithm is employed to cluster scenery.diy.163.com/professional/papers/iscas02.pdf

A comparative study on multispectral agricultural images.. - Solaiman Mouchot Brown  
The Bayesian classifier and the Hybrid Learning Vector Quantization (HLVQ) 4 neural network have very perso-iti.enst-bretagne.fr/~solaiman/Documents/Publis/Pdf/ROME95.pdf

A Texture Analysis Approach to Corrosion Image Classication - Stefan Livens Paul (1996)  
The classi#cation is performed with a Learning Vector Quantization network and comparison is made with www.ruca.ua.ac.be/visielab/papers/livens/mmm96.pdf

Computer-Aided Diagnosis for Surgical Office-Based Breast.. - Ruey-Feng Chang Phd  
on the digital US image. Then a learning vector quantization model with 24 autocorrelation texture
www.cs.ccu.edu.tw/~rfchang/soa0006.pdf

Scalable Spatial Event Representation - Tesic, Newsam, Manjunath (2002)  
label each of the dataset features. The Learning Vector Quantization (LVQ3) algorithm is iteratively
vision.ece.ucsb.edu/publications/02ICMEJelena.pdf

Learning Similarity Space - Carkacioglu, Vural (2002)  
followed by fine-ming process using learning vector quantization. Santini and Jain [4] develop a
www.ceng.metu.edu.tr/~carkaci/icip02.ps

Learning Similarity for Texture Image Retrieval - Guodong Guo Stan (2000)  
followed by a fine-tuning process using learning vector quantization. However, the performance of their markov.eee.ntu.edu.sg:8000/~szli/papers/eccv2000.ps.gz


A Coloring Method of Gray-Level Image using Neural Networks - Jang-Hee Yoo  
for image processing include LVQ (learning vector quantization)SOFM (self-organizing feature map)
garfield.etri.re.kr/~jhyoo/jhyoo/docs/coloring.ps.gz

Image classification using adaptative-learning techniques.. - Cortijo, Blanca (1996)  
the first is based on the use of learning vector quantization methods (LVQ) proposed by Kohonen
decsai.ugr.es/pub/diata/tech_rep/TR960310.ps.Z

Detection of Spectra in Objective Prism Images Using Neural.. - Smareglia, Pasian  
of this work is the so-called Dynamic Learning Vector Quantization (DLVQ) method. The idea behind this wwwas.oat.ts.astro.it/smareglia/paper/93/adass3_nn.ps.gz

A Texture Analysis Approach to Corrosion Image.. - Livens, Scheunders.. (1996)  
The classification is performed with a Learning Vector Quantization network and comparison is made with wcc.ruca.ua.ac.be/~visielab/papers/mmm.ps.gz

6.4.2. Phonetic typewriter


    • Experiments with Adaptation Methods in On-line.. - Laaksonen, Vuori.. (2000)  
      Time Warping and Levenshtein distances, Learning Vector Quantization, and Dynamically Expanding Context. 1 www.cis.hut.fi/~vuokkov/hcr/Murshed.ps
      Abstract: The purpose of this paper is to summarize our work on adaptive on-line recognition methods for handwritten characters. Reports on the work have been published in various conference proceedings and book chapters. As each publication covers only some specific part of our work, it is hard to see the whole picture and get a good overview of the whole work. Instead of trying to explain in detail all the techniques and experiments, we compare them with each other and give more general results. By...



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Dynamically Expanding Context as Committee Adaptation.. - Laaksonen, Aksela, Oja (1999)  
Adaptive Local Subspace Classifier in on-line recognition .. - Laaksonen, Aksela, Oja (1999)  
Adaptation Of Prototype Sets in On-Line Recognition of .. - Laaksonen, Vuori.. (1999)  
Adaptive Character Recognizer For A Hand-Held Device.. - Vuori, Aksela.. (2000)  
On-line Adaptation in Recognition of Handwritten.. - Vuori, Laaksonen.. (1999)  
Controlling On-Line Adaptation of a Prototype-Based.. - Vuori, Laaksonen, Oja (2000)  
Comparison of Adaptive Strategies for On-Line Character.. - Laaksonen, Hurri, Oja (1998)  


  • Citações:


An algorithm for vector quantizer design - Linde, Buzo et al. - 1980
Clustering Algorithms - Hartigan - 1975
Nearest neighbor pattern classification - Cover, Hart - 1967
Some methods for classification and analysis of multivariate.. - MacQueen - 1967
and macromolecules: the theory and practice of sequence comp.. - Sankoff, Kruskal et al. - 1983
Binary codes capable of correcting deletions - Levenshtein - 1966
volume 30 of Springer Series in Information Sciences - Kohonen - 1997   Book Details from Amazon or Barnes & Noble  
Unipen project of on-line data exchange and recognizer bench.. - Guyon, Schomaker et al. - 1994
with application to the correction of symbol strings in the .. - Kohonen, Context - 1986
Comparison of adaptive strategies for on-line character reco.. - Laaksonen, Hurri et al. - 1998
Adaptation in on-line recognition of handwriting - Vuori - 1999
Adaptation of prototype sets in on-line recognition of isola.. - Laaksonen, Vuori et al. - 1999
Experiments with a self-supervised adaptive classification s.. - Laaksonen, Hurri et al. - 1998
Short-Time Feature Vector Based Phonemic Speech Recognition .. - Torkkola - 1991
Local subspace classifier - Laaksonen - 1997
line adaptation in recognition of handwritten alphanumeric c.. - Vuori, Laaksonen et al. - 1999
Dynamically expanding context as committee adaptation method.. - Laaksonen, Aksela et al. - 1999
Adaptive local subspace classifier in on-line recognition of.. - Laaksonen, Aksela et al. – 1999


  • Site: http://www.cis.hut.fi/~vuokkov/hcr/



Adaptive On-line Recognition of Handwriting - Vuori (1998)  
On-line Adaptation in Recognition of Handwritten.. - Vuori, Laaksonen.. (1999)  
Adaptation Of Prototype Sets in On-Line Recognition of .. - Laaksonen, Vuori.. (1999)  

    • Pattern Recognition Letters Links between LVQ and.. - Frasconi, Gori, Soda (1997)  
      www.dsi.unifi.it/~paolo/ps/PRL-97-LVQ-RBF.pdf

Abstract: In this paper we show that there are some intriguing links between the Backpropagation and LVQ algorithms. We show that Backpropagation used for training the weights of radial basis function networks exhibits an increasing competitive nature as the dispersion parameters decrease. In particular, we prove that LVQ can be regarded as a competitive learning scheme taking place in radial basis function networks. () 1997 Elsevier Science B.V.




A VLSI System for Neural Bayesian and LVQ Classification - Thissen, Verleysen.. (1995)  
Successes And Failures Of Backpropagation: A Theoretical.. - Frasconi, Gori, Tesi  
Representation of Finite State Automata in Recurrent.. - Frasconi, Gori.. (1996)  


  • Site: http://www.dsi.unifi.it/~paolo/publications.html


Image Document Categorization using Hidden Tree Markov.. - Diligenti, Frasconi.. (2001)  
Text Categorization for Multi-page Documents: A Hybrid.. - Frasconi, Soda, Vullo (2001)  
Fingerprint Classification with Combinations of Support.. - Yao, Frasconi, Pontil (2001)  


    • Learning Fingerprint Minutiae Location and Type - Prabhakar, Jain, Pankanti  
      minutia classification, Gabor filters, Learning Vector Quantization. 1 Introduction The human visual
      biometrics.cse.msu.edu/prabhakar_PR3465.pdf
      Abstract: For simplicity of pattern recognition system design, a sequential approach consisting of sensing, feature extraction and classification/matching is conventionally adopted, where each stage transforms its input relatively independently. In practice, the interaction between these modules is limited. Some of the errors in this end-to-end sequential processing can be eliminated, especially for the feature extraction stage, by revisiting the input pattern. We propose a feedforward of the original...



  • Artigos Relacionados e Similares


Learning Fingerprint Minutiae Location and Type - Prabhakar, Jain, Pankanti  
Fingerprint Classification and Matching Using a Filterbank - Prabhakar  
Verification of Ink-on-paper Fingerprints by Using.. - Conti, Pilato.. (2002)  
Fingerprint Enhancement by Shape Adaptation of Scale-Space.. - Almansa, Lindeberg (1998)  
Adaptive flow orientation based feature extraction in.. - Ratha, al. (1995)  
Determination of Minutiae Scores for Fingerprint.. - Bhowmick, Bishnu..  
On the Individuality of Fingerprints - Pankanti, Prabhakar, Jain (2001)  
Minutiae Detection Through Classifier Fusion and Clustering - Carlson, Bebis, Looney  



  • Citações:


Pattern Classification - Duda, Hart et al.
LVQ PAK: A program package for the correct application of le.. - Kohonen, Kangas et al. - 1992
Goal-directed evaluation of binarization methods - Trier, Jain - 1995
An identity authentication system using fingerprints - Jain, Hong et al. - 1997
An approach to fingerprint filter design - O'Gorman, Nickerson - 1989
Adaptive flow orientation-based feature extraction in finger.. - Ratha, Chen et al. - 1995
Direct gray-scale minutiae detection in fingerprints - Maio, Maltoni - 1997
Filterbank-based fingerprint matching - Jain, Prabhakar et al. - 2000
A tree system approach for fingerprint pattern recognition - Moayer, Fu - 1986
Enhancement and feature purification of fingerprint images - Hung - 1993
Fingerprint image enhancement: algorithm and performance eva.. - Hong, Wan et al. - 1998
Edge detection in fingerprints - Verma, Majumdar et al. - 1987
Distribution of epidermal ridge minutiae - Stoney - 1988
Fingerprint image postprocessing: A combined statistical and.. - Xiao, Raafat - 1991
Fingerprint minutiae extraction from skeletonized binary ima.. - Farina, Kovacs-Vajna et al. - 1999
System and method for determining quality of fingerprint ima.. - Bolle, Pankanti et al. - 1999
Logical templates for feature extraction in fingerprint imag.. - Bhanu, Boshra - 2000
Neural network based minutiae filtering in fingerprints - Maio, Maltoni - 1998
Knowledge based fingerprint image enhancement - Luo, Tian - 2000
Learned template for feature extraction in fingerprint image.. - Bhanu, Tan - 2001



  • Site: http://biometrics.cse.msu.edu/publications.html



Learning the Human Face Concept From Black and White Pictures - Duta, Jain  
Statistical Pattern Recognition: A Review - Jain, Duin, Mao (1999)  
Face Modeling For Recognition - Hsu, Jain  


  • Site: Citeseer.nj.nec.com



Status Report Of The Finnish Phonetic Typewriter Project - Torkkola, Kangas, Utela, .. (1991)     (1 citation)
core of the basic recognition system is Learning Vector Quantization (LVQ1) 1]This algorithm was
www.cis.hut.fi/~mikkok/torkkola.icann91.ps.gz

Improving Handwritten Character Segmentation By Incorporating - Bayesian Knowledge With  
well-known machine learning methods (Learning Vector Quantization and a simplified version of the
slt.wcl.ee.upatras.gr/Publications/../papers/maragoudakis8.pdf

A Global Optimization Technique for Statistical Classifier .. - Miller, Rao, Rose, Gersho     (2 citations)
The method is compared with learning vector quantization, back propagation, several radial
rainbow.ece.ucsb.edu/current/ajit/papers/class.ps

An Adaptive Classification Scheme to Approximate.. - Encarnao Gross.. (1992)     (1 citation)
classifiers such as backpropagation or learning vector quantization (LVQ) 1/5/7/According to the
ftp.icsi.berkeley.edu/pub/techreports/1992/tr-92-047.ps.gz

Classification with Learning k-Nearest Neighbors - Laaksonen, Oja (1996)     (4 citations)
rules resemble those of the well-known Learning Vector Quantization (LVQ) method, but at the same time the www.cis.hut.fi/~jorma/papers/icnn96.ps

Transformation Invariance in Pattern Recognition -.. - Simard, Le Cun.. (1998)     (19 citations)
a survey) to learned-function such as learning vector quantization (LVQ) 17] and gradient descent.
www.research.att.com/~yann/exdb/publis/./psgz/simard-98.ps.gz

On the Analysis of Pattern Sequences by Self-Organizing Maps - Kangas (1994)     (18 citations)
Models LPC Linear Prediction Coding LVQ Learning Vector Quantization SOM Self-Organizing Map TDNN Time www.cis.hut.fi/~jari/papers/thesis94.ps.Z

Cursive Character Recognition by Learning Vector Quantization - Camastra, Vinciarelli (2001)     (1 citation)
Cursive Character Recognition by Learning Vector Quantization Francesco Camastra a Alessandro
ftp.disi.unige.it/person/CamastraF/prl01.ps

Recognition of Handwritten Digits by Combining Independent.. - Tin Kam Ho (1993)     (2 citations)
Digits by Combining Independent Learning Vector Quantizations Tin Kam Ho AT&T Bell Laboratories
www.ampl.com/who/tkh/papers/lvq.ps.gz

Combined Compression and Classification with Learning Vector.. - Baras, Dey (1998)  
Compression and Classification with Learning Vector Quantization by J. Baras, S. Dey T.R. 98-26
www.isr.umd.edu/TechReports/ISR/1998/TR_98-26/TR_98-26.pdf

Using SOMs As Feature Extractors For Speech Recognition - Kangas, Torkkola, Kokkonen (1992)  
a static pattern classifier by the Learning Vector Quantization (LVQ) algorithm [6]In reference [9]
ftp.idiap.ch/pub/papers/speech/torkkola.icassp92.ps.Z

LVQ-based Speech Recognition with High-Dimensional.. - Mäntysalo, Torkkolay..  
In this paper we have applied the Learning Vector Quantization methods, including the latest
members.home.net/torkkola/sp_papers/torkkola_icslp92_1.ps.gz

Using Phoneme Group Specific LVQ-codebooks with HMMs - Utela, Kaski, Torkkola  
design criteria are quite different. Learning Vector Quantization (LVQ) 6] is an algorithm for
ftp.idiap.ch/pub/papers/speech/torkkola.icslp92.3.ps.Z

On-line Adaptation in Recognition of Handwritten.. - Vuori, Laaksonen.. (1999)  
The reshaping algorithm is based on Learning Vector Quantization (LVQ)Four dioeerent adaptation
www.cis.hut.fi/~vuokkov/hcr/icdar_org.ps

Adaptive Character Recognizer For A Hand-Held Device.. - Vuori, Aksela.. (2000)  
ones with a method based on the Learning Vector Quantization. The adaptation process is supervised
unipen.nici.kun.nl/7th.iwfhr.2000/proceedings/postscript/paper-044-Vuori.ps

Adaptation Of Prototype Sets in On-Line Recognition of .. - Laaksonen, Vuori.. (1999)  
by utilizing a modified version of the Learning Vector Quantization (LVQ) algorithm. The presented
www.cis.hut.fi/~jorma/papers/fhr.ps

Pattern classification - Denoeux (1996)  
Coulomb Energy (RCE) 38] and Learning Vector Quantization (LVQ) 20] networks. In the RCE model, www.hds.utc.fr/~tdenoeux/revues/ncf1_1.ps
The JANUS Speech Recognizer - Rogina, Waibel (1995)     (5 citations)
nonlinear discrimiant ananlysis [8]learning vector quantization (LVQ-2) 9]and mixture size
www.is.cs.cmu.edu/~wwwadm/papers/speech/1995/SLT_95_Ivica_Rogina_1.ps.gz

Cursive Character Recognition by Learning Vector Quantization - Camastra, Vinciarelli (2000)     (1 citation)
Suisse Cursive Character Recognition by Learning Vector Quantization Francesco Camastra a b Alessandro ftp.idiap.ch/pub/reports/2000/rr00-47.ps.gz

Recognition of Unconstrained Handwritten Numerals by a Radial .. - Hwang Young-Sup  
network c K nearest neighbor d Learning vector quantization e Minimum distance classifier It
nova.postech.ac.kr/~suvia/papers/rbf_pr.ps

Comparison of Adaptive Strategies for On-Line Character.. - Laaksonen, Hurri, Oja (1998)  
features an extension of the neural Learning Vector Quantization (LVQ) algorithm to the DTW distance www.cis.hut.fi/~jorma/papers/icann98.ps

Automatic Phonetic Transcription of Words Based On Sparse Data - Wolters, van den Bosch (1997)  
again. For this second stage, we use Learning Vector Quantization (lvq, Kohonen et al.1996)lvq
ftp.cs.unimaas.nl/pub/ecml97/wolters-ftp.ps.gz

Segmental LVQ3 Training For Phoneme-Wise Tied Mixture Density HMMs - Kurimo (1996)  
the recognition of Finnish words. The Learning Vector Quantization (LVQ) methods are applied to increase www.cis.hut.fi/~mikkok/eusipco96.ps.gz

6.4.3. Creation and Intrusion Detection




    • A Hybrid Approach to Profile Creation and Intrusion Detection - Marin, Ragsdale, Surdu (2001)  
      using a competitive network called Learning Vector Quantization. Since Learning Vector Quantization is www.itoc.usma.edu/Documents/marin_rags_surdu.pdf

Abstract: Anomaly detection involves characterizing the behaviors of individuals or systems and recognizing behavior that is outside the norm. This paper describes some preliminary results concerning the robustness and generalization capabilities of machine learning methods in creating user profiles based on the selection and subsequent classification of command line arguments. We base our method on the belief that legitimate users can be classified into categories based on the percentage of commands...



  • Artigos Similares:

 
A Hybrid Approach to the Profile Creation and Intrusion.. - Marin, Ragsdale, Surdu (2001)  
Intrusion Detection: A Bibliography - Mé, Michel (2001)  
Ensemble Learning for Intrusion Detection in - Luca (2002)  
Real Time Data Mining-based Intrusion Detection - Lee, Stolfo, Chan, Eskin..  
Simulation And Agent Cooperation In Dynamic Plan Building - John Hill Department (2001)  
Implementation Oftheanticipatory Planning Support System - John Hill Department  
The Iwar Range: A Laboratory For Undergraduate.. - Schafer, Ragsdale.. (2001)  


  • Citações:


The Self-Organizing Map - Kohonen - 1992   Book Details from Amazon or Barnes & Noble  
Self-Organization and Associative Memory - Kohonen - 1987   Book Details from Barnes & Noble  
Cluster Analysis for Applications - Anderberg - 1973
Network Intrusion Detection - Biswanath, Heberlein et al. - 1994
An Intrusion-Detection Model - Denning - 1987
A Sense of Self for Unix Processes - Forrest, Hofmeyr et al. - 1996
Statistical Pattern Recognition with Neural Networks: Benchm.. - Kohonen, Barna et al. - 1988
Computer Immunology - Forrest, Hofmeyr et al. - 1997
Computer Security Threat Monitoring and Surveillance - Anderson - 1980
Concept Acquisition Through Representational Adjustment - Schlimmer - 1987
The SRI IDES statistical anomaly detector - Javitz, Valdes - 1991
Detection of Anomalous Computer Session Activity - Vaccaro, Liepins - 1989
Temporal sequence learning and data reduction for anomaly de.. - Lane, Brodley - 1999
Analysis of Four Uncertainty Calculi - Henkind, Harrison - 1989
Experience with EMERALD to Date - Neumann, Porras - 1999
Adaptive Realtime Anomaly Detection Using Inductively Genera.. - Teng, Chen et al. - 1990
ASAX: Software Architecture and Rule-based Language for Univ.. - Habra, Charlier et al. - 1992
Learning Vector Quantization for Pattern Recognition - Kohonen - 1986
Detecting Unusual Program Behavior Using the Statistical Com.. - Anderson, Lunt et al. - 1995
Intrusion Detection with Neural Networks - Ryan, Lin et al. - 1998
Design and Implementation of a Scalable Intrusion Detection .. - Jou, Gong et al. - 2000
Fuzzy Logic: Intelligence - Yen, Lengari - 1999
Intrusion Detection via System Call Traces - Kosoresow, Hofmeyr - 1997
Statistical Foundations of Audit Trail Analysis for the Dete.. - Helman, Liepins - 1993
MacMillan Technical Publishing - Bace, Detection - 2000
Proactive Anomaly Detection Using Distributed Intelligent Ag.. - Thottan, Ji - 1998
Intrusion detection Applying machine learning to Solaris aud.. - Endler - 1998
A Framework for Constructing Features and Models for Intrusi.. - Lee, Stolfo - 2000
A Data Mining and CIDF Based Approach for Detecting Novel an.. - Lee, Nimbalkar et al.
Real-time Anomaly detection Using a Nonparametric Pattern Re.. - Lankewicz, Benard - 1991
Intelligent Agents for Intrusion Detection and Countermeasur.. - Helmer, Wong et al. - 1998
Training a Neuralnetwork Based Intrusion Detector to Recogni.. - Lee, Heinbuch - 2000
EMERALD Network Intrusion Detection Project Description - Porras
Multiple Self-Organizing Maps for Intrusion Detection - Rhodes, Mahaffey et al. - 2000
EEG Classification by Learning Vector Classification - Flotzinger, Kalcher et al. - 1992
Anomaly Detection - A Soft Computing Approach - Lin - 1994
Nonparametric Classification Using Learning Vector Quantizat.. - LaVigna - 1989
MA: PWS-Kent Publishing Co - Giarratno, Riley - 1989



  • Site: http://www.ai.usma.edu/research.html



Synchronized Simulations In Planning Systems - John Hill Department (2001)  
Keywords: - Simulation Operation Monitoring  
A Hybrid Approach to the Profile Creation and Intrusion.. - Marin, Ragsdale, Surdu (2001)  


    • Using Neural Networks For The Detection, Extraction.. - Smareglia Pasian..  
      to a spectrum "head" class 2 pattern)Learning Vector Quantization)a supervised algorithm which is an
      wwwas.oat.ts.astro.it/smareglia/paper/94/vistas.ps.gz



Abstract: A system based on a multi--layer feed--forward neural network is presented, which is able to detect and extract single, multiple or overlapped spectra from objective prism images, and to perform a coarse classification. The data obtained are currently fed to subsequent wavelength calibration and detailed rule-- based classification steps. Given the encouraging results obtained, we plan to use the neural network approach to perform the immediate classification of the extracted spectra with an...



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Automated Objective Prism Spectral Classification Using.. - Pasian And Smareglia  
The ellipticities of Galactic and LMC globular clusters - Simon Goodwin  
Data Handling And Archiving At The Galileo Telescope - Balestra Pasian Pucillo  


  • Citações:


Technical Report - Kohonen, Kangas et al. - 1992
Storrie-Lombardi L - von Hippel - 1994



  • Site: http://wwwas.oat.ts.astro.it/smareglia/publist.html



The Data Flow, from Observations to the Archive.. - Pasian Smareglia..  
Luminosity Function of Early-Type Galaxies in Clusters Cores.. - Emilio Molinari  
A generalized Mosaic-to-SQL interface with extensions.. - Pasian Smareglia..  

6.4.4. Outras Aplicações


    • Limits on Learning Machine Accuracy Imposed by Data Quality - Cortes, Jackel, Chiang (1995)     (2 citations) www.research.att.com/~corinna/papers/limits.ps.gz
      Abstract: Random errors and insufficiencies in databases limit the performance of any classifier trained from and applied to the database. In this paper we propose a method to estimate the limiting performance of classifiers imposed by the database. We demonstrate this technique on the task of predicting failure in telecommunication paths.




      • Citado por:  


Bayesian Integration of Rule Models - Pedro Domingos  
GA-MINER: Parallel Data Mining with Hierarchical Genetic.. - Flockhart (1995)  



  • Artigos Relacionados e Similares


Support-Vector Networks - Cortes, Vapnik (1995)  
Communities of Interest - Corinna Cortes Daryl  
PSIDE Users' Guide - Lioen, de Swart, al. (1998)  
Programs for machine learning - Quinlan – 1993


  • Site: http://www.research.att.com/info/corinna

Giga-Mining - Corinna Cortes Daryl (1998)  
Hancock: A Language for Extracting Signatures from.. - Cortes, Fisher.. (2000)  
Support-Vector Networks - Cortes, Vapnik (1995)  



    • Competitive Winner-Takes-All Clustering in the - Domain Of Graphs   ki.cs.tuerlin.de/~bjj/papers/mlj02.ps

Abstract: We present a theoretical foundation for competitive learning in the domain of graphs within a connectionist framework. In the first part of this contribution we embed graphs in an Euclidean space to facilitate competitive learning in the domain of graphs. We adopt constitutive concepts of competitive learning like the scalar products, metrics, and the weighted mean for graphs. The first part is independent of the particular graph matching algorithm for determining the best matching model...



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Distance-based Classification of Structures within a.. - Jain, Wysotzki (2001)  
A Connectionist Approach to the Distance-Based Analysis of.. - Schädler, Wysotzki (1997)  
A Lagrangian Relaxation Network for Graph Matching - Rangarajan, Mjolsness (1996)  
Multiple Modular Networks For Recognition Of Utterances Of.. - Sekhar, Siva, Rao (1999)  
A silicon primitive for competitive learning - Hsu, Diorio (2000)  
Optimal Configuration of OSPF Aggregates - Rastogi, Breitbart, Garofalakis, .. (2002)  


  • Citações:


Computers and Intractability: A Guide to the Theory of NP-Co.. - Garey, Johnson - 1979
Self-Organization and Associative Memory - Kohonen - 1984
Computer Vision - Ballard, Brown - 1982
Self-organized formation of topologically correct feature ma.. - Kohonen - 1982
Neural computation of decisions in optimization problems - Hopfield, Tank - 1985
A graduated assignment algorithm for graph matching - Gold, Rangarajan - 1996
The ART of adaptive pattern recognition by a self-organizing.. - Carpenter, Grossberg - 1988
Structural matching in computer vision using probabilistic r.. - Christmas, Kittler et al. - 1995
IEEE Transaction on Pattern Analysis and Machine Intelligenc.. - Shapiro, Haralick et al. - 1981
Data clustering: a review - Jain, Murty et al. - 1999
An introduction to computing with neural nets - Lippman - 1987
A novel optimizing network architecture with applications - Rangarajan, Gold et al. - 1996
An image understanding system using attributed symbolic repr.. - Eshera, Fu - 1986
Entropy and distance of random graphs with application to st.. - Wong, You - 1985
Matching hierarchical structures using association graphs - Pelillo, Siddiqi et al. - 1999
A Lagrangian relaxation network for graph matching - Rangarajan, Mjolsness - 1996
The maximum clique problem - Bomze, Budinich et al. - 1999
An eigen decomposition approach to weighted graph matching p.. - Umeyama - 1988
Learning relational concepts with decision trees - Geibel, Wysotzki - 1996
Supervised neural networks for the classification of structu.. - Sperduti, Starita - 1997
Learning with preknowledge: Clustering with point and graph .. - Gold, Rangarajan et al. - 1995
relational learning with decision trees - Geibel, Wysotzki - 1996
An analysis of recent work on clustering algorithms - Fasulo - 1999
a certain distance between the isomorphism classes of graphs - Zelinka - 1975
Recent developments in graph matching - Bunke - 2000
Relaxation by the hopfield neural network - Yu, Tsai - 1992
A massively parallel architecture for a selforganising neura.. - Carpenter, Grossberg - 1987
Pattern recognition by graph matching using potts mft networ.. - Suganthan, Teoh et al. - 1995
Fuzzy graphs - Rosenfeld - 1975
Graphmetriken und Distanzgraphen - Kaden - 1982
Graph-based hierarchical conceptual clustering - Jonyer, Holder et al. - 2001
A connectionist approach to structural similarity determinat.. - Schadler, Wysotzki - 1997
the short-term-memory of WTA nets - Jain, Wysotzki - 2001
Comparing structures using a Hopfield-style neural network - Schadler, Wysotzki - 1999
IEEE Transactions on Information Theory - Gersho, structure et al. - 1982
Die Ermittlung struktureller Ahnlichkeit und struktureller M.. - Schadler - 1999
Efficient pattern discrimination with inhibitory WTA nets - Jain, Wysotzki - 2001
Fast winner-takes-all networks for the maximum clique proble.. - Jain, Wysotzki - 2002
Weighted mean of a pair of graphs - Bunke, Gunter - 2001
Distance-based classification of structures within a connect.. - Jain, Wysotzki - 2001
ART 2: Self-organisation of stable category recognition code.. - Carpenter, Grossberg - 1987
Adaptive self-organizing map in the graph domain - Gunter, Bunke - 2002
Winner-takes-all classification of structures - Jain, Wysotzki - 2003
Self-organizing map for clustering in the graph domain - Gunter, Bunke - 2002
Self-organizing recognition and classification of relational.. - Jain, Wysotzki - 2002
Recent advances in structural pattern recognition with appli.. - Bunke - 2001
Heuristics for similarity searching of chemical graphs using.. - Raymond, Gardiner et al. - 2002
Synthesis of function-described graphs and clustering of att.. - Serratosa, Alquezar et al. - 2002



  • Site: http://ki.cs.tu-berlin.de/~bjj/



Efficient Pattern Discrimination with Inhibitory WTA Nets - Jain, Wysotzki (2001)  
Distance-based Classification of Structures within a.. - Jain, Wysotzki (2001)  
Fast Winner-Takes-All Networks for the Maximum Clique Problem - Jain, Wysotzki (2002)  



    • Efficient Low-Level Vision Program - Design Using Sub-Machine-Code (2002)  
      symbolrecognition module is based on a Learning Vector Quantization neural network that classifies the
      www-dii.ing.unisi.it/aiia2002/paper/PERCEVISIO/adorni-aiia02.pdf
      Abstract: Sub-machine-code Genetic Programming (SmcGP) is a variant of GP aimed at exploiting the intrinsic parallelism of sequential CPUs.



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Solving Even-12, -13, -15, -17, -20 and-22 Boolean Parity.. - Riccardo Poli (1999)  
Smooth Uniform Crossover, Sub-Machine Code GP and Demes: A.. - Poli, Page (1999)  
Solving High-Order Boolean Parity Problems with Smooth Uniform.. - Poli, Page (2000)  

Omnidirectional Vision Algorithms in Robotics - Adorni, Cagnoni, Carletti.. (2002)  
Sub-Machine-Code GP: New Results and Extensions - Poli (1999)  
Efficient Evolution of Parallel Binary Multipliers and Continuous.. - Poli (1998)  


  • Citações:



Genetic Programming: On the Programming of Computers by Mean.. - Koza - 1992
Self-organization and associative memory - Kohonen - 1988
Genetic Programming: An Introduction - Banzhaf, Francone et al. - 1998
Sub-machine-code Genetic Programming - Poli, Langdon - 1999
Sub-machine-code GP: New results and extensions - Poli - 1999
License-plate recognition for restricted-access area control.. - Adorni, Bergenti et al. - 2000
Access control system with neuro-fuzzy supervision - Adorni, Cagnoni et al.
available via anonymou ftp from ftpgarage - Punch, user et al. - 1996
OSLVQ: a training strategy for optimum-size Learning Vector .. - Cagnoni, Valli - 1994
Efficient low-resolution character recognition using Sub-mac.. - Adorni, Cagnoni et al. - 2001
Application of genetic programming for multicategory pattern.. - Kishore, Patnaik et al.



  • Site: http://www-dii.ing.unisi.it/aiia2002/paper.htm



Evidence Accumulation Method for Mobile Robot Localization - Restelli, Sorrenti, Marchese (2002)  
Towards An Adaptive Mail Classifier - Manco, Masciari, Ruffolo, Tagarelli (2002)  
Recupero di immagini tramite trasformata di Hough - Anelli Micarelli Sangineto (2002)  


    • Semiconductor Defect Classification using Hyperellipsoid.. - Kameyama, Kosugi  
      the/ nearest neighbor algorithm [2] and learning vector quantization [9]and those based on class borders
      emerald.is.tsukuba.ac.jp/kameyama/common/publications/kameyama-IJCNN99.pdf
      Abstract: An automatic defect classification (ADC) system for visual inspection of semiconductor wafers, using a neural network classifier is introduced. The proposed Hyperellipsoid Clustering Network (HCN) employing a Radial Basis Function (RBF) in the hidden layer, is trained with additional penalty conditions for recognizing unfamiliar inputs as originating from an unknown defect class. Also, by using a dynamic model alteration method called Model Switching, a reduced-model classifier which enables an ...



  • Artigos Similares:

 
An Algorithm for Model Determination in a Layered Network.. - Kameyama, Kosugi  
A Note on Shape Matching using a Constructive Relaxation.. - Kameyama, Toraichi, Kosugi  
Image Matching based on Relaxation and Model Switching on.. - Kameyama, Toraichi  
Model Switching by Channel Fusion for Network Pruning and.. - Kameyama, Kosugi (1998)  
Relaxation with Model Switching and its application to.. - Kameyama, Toraichi.. (2002)  
Constructive Relaxation Matching Involving Dynamical Model.. - Kameyama, Toraichi  


  • Citações:



Introduction to Statistical Pattern Recogni- tion - Fukunaga - 1990
Self-organization and associative memory - Kohonen - 1988
Statistical Learning Theory - Vapnik - 1999
Networks for approximation and learning - Poggio, Girosi - 1990
Fast learning in networks of locally-tuned processing units - Moody, Darken - 1989
On estimation of a probability density function and mode - Parzen - 1962
Pattern Classi cation and Scene Analysis - Duda, Hart - 1973
Pruning algorithms a survey - Reed - 1993
Color image quantization for frame buffer display - Heckbert - 1982
and the PDP Research Group - Rumelhart, McClelland - 1986
Neural network pruning by fusing hidden layer units - Kameyama, Kosugi - 1991
Model switching by channel fusion for network pruning and ef.. - Kameyama, Kosugi - 1998
Automatic defect classi cation for semicon- ductor manufactu.. - Chou, Rao et al. - 1997
Automatic defect classi cation in visual inspection of semic.. - Kameyama, Kosugi et al. - 1998



  • Site: http://emerald.is.tsukuba.ac.jp/kameyama/common/publications.html


An Algorithm for Model Determination in a Layered Network.. - Kameyama, Kosugi  
A Neural Network Incorporating Adaptive Gabor Filters for .. - Kameyama, Mori, Kosugi (1997)  
Automatic Fusion and Splitting of Artificial Neural Elements .. - Kameyama, Kosugi  



    • Learning Vector Quantization for Multimodal Data - Hammer, Strickert, Villmann  
      Learning Vector Quantization for Multimodal Data Barbara Hammer
      www.informatik.uni-osnabrueck.de/barbara/papers/postscripts/icannsrng_02.ps.gz
      Abstract: Learning vector quantization (LVQ) as proposed by Kohonen is a simple and intuitive, though very successful prototype-based clustering algorithm.



  • Artigos Similares:

 
Batch-RLVQ - Hammer, Villmann  
Input pruning for neural gas architectures - Hammer, Villmann  
Rule Extraction from Self-Organizing Networks - Hammer, Rechtien, Strickert..  
Estimating Relevant Input Dimensions for Self-organizing.. - Hammer, Villmann (2001)  
Generalized Relevance LVQ for Time Series - Strickert, Bojer, Hammer  
Supervised Neural Gas for Learning Vector Quantization - Villmann, Hammer, Strickert  


  • Citações:


Self-Organizing Maps - Kohonen - 1997
Neural-gas' network for vector quantization and its applicat.. - Martinetz, Berkovich et al. - 1993
Self-organizing maps: generalizations and new optimization t.. - Graepel, Burger et al. - 1998
Generalized learning vector quantization - Sato, Yamada - 1995
The enhanced LBG algorithm - Patane, Russo - 2001
Estimating relevant input dimensions for self-organizing alg.. - Hammer, Villmann - 2001
Toplogy Preservation in SelfOrganizing Feature Maps: Exact D.. - Villmann, Der and et al. - 1997
A greedy algorithm for Gaussian mixture learning - Vlassis, Likas - 2002



  • Site: http://www.informatik.uni-osnabrueck.de/barbara/papers/pub_hammer.html



Recurrent Networks for Structured Data - a Unifying Approach and.. - Hammer  
Relevance Determination in Learning Vector Quantization - Bojer, Hammer, Schunk..  
Estimating Relevant Input Dimensions for Self-organizing.. - Hammer, Villmann (2001)  


    • Generalized Relevance LVQ for Time Series - Strickert, Bojer, Hammer  
      recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling www.informatik.uni-osnabrueck.de/barbara/papers/postscripts/icann_01_marc.ps.gz
      Abstract: An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use GRLVQ for two tasks: first, for obtaining a phase space embedding of a scalar time series, and second, for short term and long term data prediction. The proposed embedding method is tested with a signal from the wellknown Lorenz system. Afterwards, it is applied to daily lysimeter observations of water runoff. A one-step...



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A neural network architecture for the categorization of.. - Tijsseling, Berthouze  
Tutte Polynomials in Square Grids - Noy (2000)  
Triangulating with High Connectivity - Dey, Dillencourt, Ghosh, Cahill (1995)  
Learning Vector Quantization for Multimodal Data - Hammer, Strickert, Villmann  
Rule Extraction from Self-Organizing Maps - Hammer, Rechtien, Strickert..  
Rule Extraction from Self-Organizing Networks - Hammer, Rechtien, Strickert..  


  • Citações:


Self-Organizing Maps - Kohonen - 1997   Book Details from Amazon or Barnes & Noble  
Generalized learning vector quantization - Sato, Yamada - 1995
Annals of Mathematics - Whitney, Manifolds - 1936
Schmidhuber: Long short-term memory - Hochreiter - 1997
Swinney: Independent Coordinates for Strange Attractors from.. - Fraser - 1986
Lecture Notes in Mathematics Vol - Takens, Attractors et al. - 1981
Villmann: Estimating relevant input dimensions for self-orga.. - Hammer - 2001
Birattari: A Multi-Step-Ahead Prediction Method Based on Loc.. - Bontempi - 2000
Schreiber: Nonlinear time series analysis - Kantz - 1997
Abarbanel: Determining embedding dimension for phase-space r.. - Kennel, Brown - 1992
Neural Network World - Dorffner, for et al. - 1996
of Atmospheric Sc - Lorenz, Flow - 1963


  • Site: http://www.informatik.uni-osnabrueck.de/barbara/papers/pub_hammer.html



Recurrent Networks for Structured Data - a Unifying Approach and.. - Hammer  
Relevance Determination in Learning Vector Quantization - Bojer, Hammer, Schunk..  
Estimating Relevant Input Dimensions for Self-organizing.. - Hammer, Villmann (2001)  


    • Combining Neural Gas and Learning Vector Quantization for.. - Camastra, al. (2001)  
      - Suisse Combining Neural Gas and Learning Vector Quantization for Cursive Character Recognition ftp.idiap.ch/pub/reports/2001/rr01-18.ps.gz
      Abstract: This paper presents a cursive character recognizer, a crucial module in any Cursive Script Recognition system based on a segmentation and recognition approach. The character classi cation is achieved by combining the use of Neural Gas (NG) and Learning Vector Quantization (LVQ). NG is used to verify whether lower and upper case version of a certain letter can be joined in a single class or not. Once this is done for every letter, it is possible to nd an optimal number of classes maximizing the ...



  • Artigos Similares:


Cursive Character Recognition by Learning Vector Quantization - Camastra, Vinciarelli (2001)  
Intrinsic Dimension Estimation of Data: An Approach Based.. - Camastra, Vinciarelli (2000)  
A new normalization technique for cursive handwritten words - Vinciarelli, Lüttin (2000)  
Writer adaptation techniques in HMM based Off-Line Cursive.. - Vinciarelli, al.  


  • Site: http://www.idiap.ch/~vincia/publications.html



Offline Cursive Word Recognition using Continuous Density.. - Vinciarelli, al. (2001)  
Intrinsic Dimension Estimation of Data: An Approach Based.. - Camastra, Vinciarelli (2000)  
Cursive Character Recognition by Learning Vector Quantization - Camastra, Vinciarelli (2000)  

    • Australian Machine Learning Workshop - Hosted By The  
      National University Maximum margin learning vector quantization Lawrence Buckingham and Shlomo Geva discus.anu.edu.au/~bartlett/amlw99/schedule.ps
      Abstract: This paper explores the possibility of designing algorithms speci cally for large data sets. Speci cally, the paper looks at how increasing data set size a ects bias and variance error decompositions for classi cation algorithms. Preliminary results of experiments to determine these e ects are presented, showing that, as hypothesised, variance can be expected to decrease as training set size increases. No clear e ect of training set size on bias was observed. These results have profound...



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Addressing the Learnability of Verb Subcategorizations with.. - Mike Dowman Mike (2000)  
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Common Control Principles Of Basal Ganglia - Thalamocortical.. - Lörincz (1996)  
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The BBG Rule Induction Algorithm - Kevin Van Horn  
Comparative evaluation of alternative induction engines for.. - Geoffrey Webb (1997)  
OPUS: An Efficient Admissible Algorithm for Unordered Search - Webb (1995)  


  • Citações:


Programs for Machine Learning - Quinlan - 1992
Learnability and Cognition The Acquisition of Argument Struc.. - Pinker - 1989   Book Details from Barnes & Noble  
ective Rule Induction - Cohen, Fast - 1995
Automatic Grammar Induction and Parsing Free Text: A Transfo.. - Brill
Bayesian Learning of Probabilistic Language Models - Stolcke - 1994
Language Identication in the Limit - Gold - 1967
Knowledge of Language - Chomsky - 1986
The Machine Learning of Phonological Structure - Ellison - 1992
Language and Number The Emergence of a Cognitive System - Hurford - 1987
A Cross-linguistic Computational Investigation of the Learna.. - Dowman - 1998
An Introduction to Functional Grammar Second Edition - Halliday - 1994




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