Gader, P.D.,
Khabou, M.A.,
Automatic Feature Generation for Handwritten Digit Recognition,
PAMI(18), No. 12, December 1996, pp. 1256-1261.
IEEE Abstract. IEEE Top Reference.
WWW Version.
9701
Neural Networks. Two different measures, orthogonality and information, guide the search
for features to use in the NN implementation.
Uses multiple classifiers. Recognition rates are around 98% on a test set
with 1000 digits per class.
BibRef
Chiang, J.H.,
Gader, P.D.,
A Hybrid Feature Extraction Framework for
Handwritten Numeric Fields Recognition,
ICPR96(IV: 436-440).
WWW Version.
9608(Ind. Tech. Res. Institute, ROC)
BibRef
Knerr, S.,
Personnaz, L., and
Dreyfus, G.,
Handwritten Digit Recognition by Neural Networks with
Single-Layer Training,
TNN(3), No. 6, November 1992, pp. 962-968.
BibRef
9211
Calabro, C.,
Ferragina, P.,
Granieri, M.N.,
Recognition of Hand-Written Rotated Digits by Neural Networks,
MVA(8), No. 5, 1995, pp. 351-357.
HTML Version.
BibRef
9500
Lee, S.W.[Seong-Whan],
Off-Line Recognition of Totally Unconstrained Handwritten Numerals
Using Multilayer Cluster Neural-Network,
PAMI(18), No. 6, June 1996, pp. 648-652.
IEEE Abstract. IEEE Top Reference.
WWW Version.
9607
BibRef
Earlier:
Add
Kim, Y.J.[Young Joon], :
ICPR94(B:507-509).
WWW Version.
9410
BibRef
Lee, S.W.,
Kim, C.H.,
Ma, H.,
Tang, Y.Y.,
Multiresolution Recognition of Unconstrained Handwritten Numerals with
Wavelet Transform and Multilayer Cluster Neural-Network,
PR(29), No. 12, December 1996, pp. 1953-1961.
WWW Version.
9701
Wavelets.
Neural Networks.
BibRef
Cho, S.B.,
Neural-Network Classifiers for Recognizing Totally
Unconstrained Handwritten Numerals,
TNN(8), No. 1, January 1997, pp. 43-53.
9701
BibRef
Earlier:
Recognition Of Unconstrained Handwritten Numerals by
Doubly Self-Organizing Neural Network,
ICPR96(IV: 426-430).
WWW Version.
9608(Yonsei Univ., KOR)
BibRef
Cao, J.,
Ahmadi, M.,
Shridhar, M.,
A Hierarchical Neural-Network Architecture for
Handwritten Numeral Recognition,
PR(30), No. 2, February 1997, pp. 289-294.
WWW Version.
9704
BibRef
Cao, J.,
Shridhar, M.,
Kimura, F.,
Ahmadi, M.,
Statistical and neural classification of handwritten numerals: a
comparative study,
ICPR92(II:643-646).
WWW Version.
9208
BibRef
Reddy, N.V.S.,
Nagabhushan, P.,
A 3-Dimensional Neural-Network Model for
Unconstrained Handwritten Numeral Recognition: A New Approach,
PR(31), No. 5, May 1998, pp. 511-516.
WWW Version.
9805
BibRef
Hwang, Y.S.[Young-Sup],
Bang, S.Y.[Sung-Yang],
Recognition of Unconstrained Handwritten Numerals by a
Radial Basis Function Neural Network Classifier,
PRL(18), No. 7, July 1997, pp. 657-664.
9711
BibRef
Earlier:
An Efficient Method to Construct a Radial Basis Function
Neural Network Classifier and its Application to Unconstrained
Handwritten Digit Recognition,
ICPR96(IV: 640-644).
WWW Version.
9608(Pohang Institute of Science, KOR)
BibRef
Lee, S.W.,
Kim, S.Y.,
Integrated Segmentation and Recognition of Handwritten Numerals with
Cascade Neural Network,
SMC-C(29), No. 2, May 1999, pp. 285.
IEEE Top Reference.
BibRef
9905
Zhou, J.[Jie],
Gan, Q.A.[Qi-Ang],
Krzyzak, A.[Adam],
Suen, C.Y.[Ching Y.],
Recognition of handwritten numerals by Quantum Neural Network with
fuzzy features,
IJDAR(2), No. 1, 1999, pp. 30-36.
BibRef
9900
Wang, J.G.[Jian-Guo],
Yan, H.[Hong],
A hybrid method for unconstrained handwritten numeral recognition by
combining structural and neural 'gas' classifiers,
PRL(21), No. 6-7, June 2000, pp. 625-635.
0006 See also Model-Based Segmentation Method for Handwritten Numeral Strings, A.
BibRef
Zhang, B.L.[Bai-Ling],
Fu, M.Y.[Min-Yue],
Yan, H.[Hong],
A nonlinear neural network model of mixture of local principal
component analysis: application to handwritten digits recognition,
PR(34), No. 2, February 2001, pp. 203-214.
WWW Version.
0011
BibRef
Zhang, B.L.[Bai-Ling],
Fu, M.Y.[Min-Yue],
Yan, H.[Hong],
A Modular Classification Scheme with Elastic Net Models for
Handwritten Digit Recognition,
ICPR98(Vol II: 1859-1861).
WWW Version.
9808
BibRef
Wong, K.W.[Kwok-Wo],
Leung, C.S.[Chi-Sing],
Chang, S.J.[Sheng-Jiang],
Handwritten digit recognition using multi-layer feedforward neural
networks with periodic and monotonic activation functions,
ICPR02(III: 106-109).
WWW Version.
0211
BibRef
Kim, H.Y.[Ho-Yon],
Lim, K.T.[Kil-Taek],
Nam, Y.S.[Yun-Seok],
Handwritten numeral string recognition using neural network classifier
trained with negative data,
FHR02(395-400).
IEEE Top Reference.
0209
BibRef
Lim, K.T.[Kil-Taek],
Chien, S.I.[Sung-Il],
Neural Network Based Feature Space Generation for
Multiple Databases of Handwritten Numerals,
ICPR98(Vol I: 375-377).
WWW Version.
9808
BibRef
Kawaguchi, T.,
Nagata, R.I.,
Miyake, Y.[Yasuji],
Inoue, S.,
Wakabayashi, T.[Tetsushi],
Kimura, F.[Fumitaka],
Tsuruoka, S.,
Handwritten Numeral Recognition Using
Autoassociative Neural Networks,
ICPR98(Vol I: 166-171).
WWW Version.
9808
BibRef
Lin, X.,
Ding, X.,
Wu, Y.,
Handwritten Numeral Recognition Using MFNN Based Multiexpert
Combination Strategy,
ICDAR97(Poste)
9708
BibRef
Lee, S., and
Pan, J.C.,
Handwritten Numeral Recognition Based on Hierarchically
Self-Organizing Learning Networks with Spatio-Temporal Pattern Recognition,
CVPR92(176-182).
IEEE Abstract. IEEE Top Reference.
BibRef
9200
Williams, C.K.I.,
Combining Deformable Models and Neural Networks for
Handprinted Digit Recognition,
Ph.D.Thesis, 1994,
BibRef
9400
Toronto
BibRef
Lemarie, B.,
Practical Implementation of a Radial Basis Function Network for
Handwritten Digit Recognition,
ICDAR93(412-415).
BibRef
9300
Tsay, S.C.[Shuh-Chuan],
Hong, P.R.[Peir-Ren],
Chieu, B.C.[Bin-Chang],
Handwritten digits recognition system via OCON neural network by
pruning selective update,
ICPR92(II:656-659).
WWW Version.
9208
BibRef
Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Money and Check Processing -- Amounts, etc. .