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Performance evaluation of pattern classifiers for handwritten character recognition

https://doi.org/10.1007/s100320200076

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Aspect Ratio Adaptive Normalization for Handwritten Character Recognition

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Sorting and Recognizing Cheques and Financial Documents

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Pattern Classification

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The Nature of Statistical Learning Theory

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Segmentation-recognition algorithm for zip code field recognition

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A statistical decision rule with incomplete knowledge about classes

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Evaluation of pattern classifiers for fingerprint and OCR applications

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Feature extraction methods for character recognition-A survey

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Subspace methods of pattern recognition

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A note on comparing classifiers

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Probabilistic neural networks

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A subspace projection approach to feature extraction: The two-dimensional gabor transform for character recognition

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Introduction to Statistical Pattern Recognition

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Evaluation of prototype learning algorithms for nearest-neighbor classifier in application to handwritten character recognition

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Off-line handwritten numeral string recognition by combining segmentation-based and segmentation-free methods

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A hybrid neural network model in handwritten word recognition

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A Tutorial on Support Vector Machines for Pattern Recognition

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Learning representations by back-propagating errors

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Supervised and unsupervised learning in radial basis function classifiers

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Pattern Classification: A Unified View of Statistical and Neural Approaches

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Regularized Discriminant Analysis

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Neural and fuzzy methods in handwriting recognition

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A survey of methods and strategies in character segmentation

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Off-line, handwritten numeral recognition by perturbation method

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Probabilistic visual learning for object representation

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Are multilayer perceptrons adequate for pattern recognition and verification?

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Statistical pattern recognition: a review

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Handwritten word recognition with character and inter-character neural networks

inferredcites →https://doi.org/10.1109/5.156471openalex-snapshot

Segmentation methods for character recognition: from segmentation to document structure analysis

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Neural and statistical classifiers-taxonomy and two case studies

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Modeling the manifolds of images of handwritten digits

inferredcites →https://doi.org/10.1109/78.175747openalex-snapshot

Discriminative learning for minimum error classification (pattern recognition)

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GradientBased Learning Applied to Document Recognition

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Handwritten ZIP code recognition using lexicon free word recognition algorithm

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A new distinguishing algorithm of connected character image based on Fourier transform

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Handwritten numeral recognition using autoassociative neural networks

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Improved versions of learning vector quantization

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Modified Quadratic Discriminant Functions and the Application to Chinese Character Recognition

inferredcites →https://doi.org/10.1142/9789812797650_0040openalex-snapshot

PERFORMANCE COMPARISON OF STATISTICAL AND NEURAL NETWORK CLASSIFIERS IN HANDWRITTEN DIGITS RECOGNITION

inferredcites →https://doi.org/10.1142/9789812830968_0002openalex-snapshot

PATTERN CLASSIFICATION TECHNIQUES BASED ON FUNCTION APPROXIMATION

inferredcites →https://doi.org/10.1162/neco.1993.5.3.367openalex-snapshot

Improving Rejection Performance on Handwritten Digits by Training with “Rubbish”

inferredcites →https://doi.org/10.57702/yobif9bgopenalex-snapshot

Gradient-based learning applied to document recognition

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Neural networks for pattern recognition

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