25.4.6.5 Arabic Numbers, Digits, Handwritten, Numeral Recognition

Chapter Contents (Back)
OCR. Digits. Numbers. Character Recognition. Handwritten Digits.

The Street View House Numbers (SVHN) Dataset ,
2011 WWW Link.
Dataset, House Numbers. 600,000 digit images.

Bakis, R., Herbst, N.M., and Nagy, G.,
A Experimental Study of Machine Recognition of Hand-Printed Numerals,
SSC(4), No. 2, July 1968, pp. 119-132. N-Tuple Matching system for OCR. BibRef 6807

Siy, P., Chen, C.S.,
Fuzzy Logic for Handwritten Numeral Character Recognition,
SMC(4), 1974, pp. 570-575. BibRef 7400

Pavlidis, T., and Ali, F.,
Computer Recognition of Handwritten Numerals by Polygonal Approximations,
SMC(7), 1975, pp. 610-614. Polygonal Approximation. BibRef 7500

Impedovo, S., Marangelli, B., Plantamura, V.L.,
Real Time Recognition of Handwritten Numerals,
SMC(6), No. 2, February 1976, pp. 145-148. BibRef 7602

Impedovo, S., Fanelli, A.M., Marangelli, B.,
A Fourier Descriptor Set for Recognizing Non-Stylized Numerals,
SMC(8), No. 8, August 1978, pp. 640-645. BibRef 7808

Impedovo, S., Fanelli, A.M.,
Interactive System for Hand-Written Numeral Classification Based on Fourier Descriptors,
CIAP80(135-139). BibRef 8000

Impedovo, S., Abbattista, N.,
Hand-Written Numeral Recognition : The Organization Degree Measurement,
ICPR82(40-43). BibRef 8200

Dimauro, G., Impedovo, S., Modugno, R., Pirlo, G.,
Numeral recognition by weighting local decisions,
ICDAR03(1070-1074).
IEEE DOI 0311

See also Multi-expert verification of hand-written signatures. BibRef

Dimauro, G., Impedovo, S., Pirlo, G., Salzo, A.,
Zoning design for handwritten numeral recognition,
CIAP97(II: 592-599).
Springer DOI 9709
BibRef

Impedovo, S., Dimauro, G.,
An interactive system for the selection of handwritten numeral classes,
ICPR90(I: 563-566).
IEEE DOI 9006
BibRef

Impedovo, S., Pirlo, G.,
Class-oriented recognizer design by weighting local decisions,
CIAP03(676-681).
IEEE DOI 0310
BibRef

Shridhar, M., Badreldin, A.,
Handwritten Numeral Recognition by Tree Classification Methods,
IVC(2), No. 3, August 1984, pp. 143-149.
Elsevier DOI BibRef 8408
And:
A Tree Classification Algorithm for Handwritten Character Recognition,
ICPR84(615-618). BibRef

Shridhar, M., Badreldin, A.,
Recognition of Isolated and Simply Connected Handwritten Numerals,
PR(19), No. 1, 1986, pp. 1-12.
Elsevier DOI BibRef 8600

Shridhar, M., Badreldin, A.,
Context-Directed Segmentation Algorithm for Handwritten Numeral Strings,
IVC(5), No. 1, February 1987, pp. 3-9.
Elsevier DOI BibRef 8702

Shridhar, M., Badreldin, A.,
A High-Accuracy Syntactic Recognition Algorithm for Handwritten Numerals,
SMC(15), 1985, pp. 152-158. BibRef 8500

Huang, J.S., Chuang, K.,
Heuristic Approach to Handwritten Numeral Recognition,
PR(19), No. 1, 1986, pp. 15-19.
Elsevier DOI BibRef 8600

Ray, S.,
A Heuristic Noise Reduction Algorithm Applied to Handwritten Numeric Characters,
PRL(7), 1988, pp. 9-12. BibRef 8800

Baptista, G., Kulkarni, K.M.,
A High Accuracy Algorithm for Recognition of Handwritten Numerals,
PR(21), No. 4, 1988, pp. 287-291.
Elsevier DOI BibRef 8800

Gader, P.D., Forester, B., Ganzberger, M., Billies, A., Mitchell, B., Whalen, M., and Yocum, T.,
Recognition of Handwritten Digits Using Template and Model Matching,
PR(24), No. 5, 1991, pp. 421-431.
Elsevier DOI BibRef 9100

Westall, J.M., and Narasimha, M.S.,
Vertex Directed Segmentation of Handwritten Numerals,
PR(26), No. 10, October 1993, pp. 1473-1486.
Elsevier DOI BibRef 9310

Gupta, A., Nagendraprasad, M.V., Liu, A., Wang, P.S.P., and Ayyadurai, S.,
An Integrated Architecture for Recognition of Totally Unconstrained Handwritten Numerals,
PRAI(7), No. 4, 1993, pp. 757-773. BibRef 9300

Yan, H.,
Handwritten Digit Recognition Using an Optimized Nearest-Neighbor Classifier,
PRL(15), No. 2, February 1994, pp. 207-211. BibRef 9402

Yan, H.[Hong],
Prototype optimization for nearest neighbor classifiers using a two-layer perceptron,
PR(26), No. 2, February 1993, pp. 317-324.
Elsevier DOI 0401
BibRef

AbuHaiba, I.S.I., Ahmed, P.,
A fuzzy graph theoretic approach to recognize the totally unconstrained handwritten numerals,
PR(26), No. 9, September 1993, pp. 1335-1350.
Elsevier DOI 0401
BibRef

Chi, Z.R., Yan, H.,
Handwritten Numeral Recognition Using a Small Number of Fuzzy Rules with Optimized Defuzzification Parameters,
NeurNet(8), No. 5, 1995, pp. 821-827. BibRef 9500

Chi, Z.R., Suters, M., Yan, H.,
Handwritten Digit Recognition Using Combined ID3-Derived Fuzzy Rules and Markov-Chains,
PR(29), No. 11, November 1996, pp. 1821-1833.
Elsevier DOI 9612
BibRef

Chi, Z.[Zheru], Wu, J.[Jing], Yan, H.[Hong],
Handwritten numeral recognition using self-organizing maps and fuzzy rules,
PR(28), No. 1, January 1995, pp. 59-66.
Elsevier DOI 0401
BibRef

Cheng, D.H., Yan, H.,
Recognition of Handwritten Digits Based on Contour Information,
PR(31), No. 3, March 1998, pp. 235-255.
Elsevier DOI 9802
BibRef

Hu, J.M., Yan, H.,
Structural Primitive Extraction and Coding for Handwritten Numeral Recognition,
PR(31), No. 5, May 1998, pp. 493-509.
Elsevier DOI 9805
BibRef

Hu, J.M.[Jian-Ming], Yan, H.[Hong],
A Model-Based Segmentation Method for Handwritten Numeral Strings,
CVIU(70), No. 3, June 1998, pp. 383-403.
DOI Link
See also hybrid method for unconstrained handwritten numeral recognition by combining structural and neural gas classifiers, A. BibRef 9806

Hu, J.M., Yu, D.G., Yan, H.,
A Multiple Point Boundary Smoothing Algorithm,
PRL(19), No. 8, June 1998, pp. 657-668. 9808
BibRef

Hu, J.M.[Jian-Ming], Yu, D.G.[Dong-Gang], Yan, H.[Hong],
Construction of partitioning paths for touching handwritten characters,
PRL(20), No. 3, March 1999, pp. 293-303. BibRef 9903

Yu, D.G.[Dong-Gang], Yan, H.[Hong], Hu, J.M.[Jian-Ming],
Algorithms for Partitioning Path Construction of Handwritten Numeral Strings,
ICPR98(Vol I: 372-374).
IEEE DOI 9808
BibRef

Wakahara, T.,
Shape-Matching Using LAT and its Application to Handwritten Numeral Recognition,
PAMI(16), No. 6, June 1994, pp. 618-629.
IEEE DOI BibRef 9406

Wakahara, T.,
Multi-template GAT correlation for character recognition with a limited quantity of data,
ICDAR05(II: 824-828).
IEEE DOI 0508
BibRef
Earlier:
Shape matching using GAT correlation against nonlinear distortion and its application to handwritten numeral recognition,
ICDAR03(54-59).
IEEE DOI 0311

See also Online Cursive Kanji Character Recognition Using Stroke Based Affine Transformation. BibRef

Yamashita, Y.[Yukihiko], Wakahara, T.[Toru],
Subspace Methods with Globally/Locally Weighted Correlation Matrix,
ICPR10(4259-4262).
IEEE DOI 1008

See also Affine-Invariant Recognition of Handwritten Characters via Accelerated KL Divergence Minimization. BibRef

Wakahara, T.[Toru], Yamashita, Y.[Yukihiko],
k-NN classification of handwritten characters via accelerated GAT correlation,
PR(47), No. 3, 2014, pp. 994-1001.
Elsevier DOI 1312
BibRef
Earlier: FHR12(143-148).
IEEE DOI 1302
BibRef
Earlier:
Affine-Invariant Recognition of Handwritten Characters via Accelerated KL Divergence Minimization,
ICDAR11(1095-1099).
IEEE DOI 1111
BibRef
Earlier:
Multi-template GAT/PAT Correlation for Character Recognition with a Limited Quantity of Data,
ICPR10(2873-2876).
IEEE DOI 1008
Affine-invariant template matching BibRef

Yamashita, Y.[Yukihiko], Wakahara, T.[Toru],
Affine-transformation and 2D-projection invariant k-NN classification of handwritten characters via a new matching measure,
PR(52), No. 1, 2016, pp. 459-470.
Elsevier DOI 1601
BibRef
Earlier: A2, A2:
Enhanced GPT Correlation for 2D Projection Transformation Invariant Template Matching,
GCPR15(435-445).
Springer DOI 1511
BibRef
Earlier: A2, A2:
GPT Correlation for 2D Projection Transformation Invariant Template Matching,
ICPR14(3810-3815)
IEEE DOI 1412
BibRef
And: A1, A2:
k-NN Classification of Handwritten Characters Using a New Distortion-Tolerant Matching Measure,
ICPR14(262-267)
IEEE DOI 1412
Matching. Computational modeling. Acceleration BibRef

Bailey, R.R., Srinath, M.,
Orthogonal Moment Features for Use with Parametric and Nonparametric Classifiers,
PAMI(18), No. 4, April 1996, pp. 389-399.
IEEE DOI Moments. 9605
BibRef

Heikkonen, J., Mantynen, N.,
A Computer Vision Approach to Digit Recognition on Pulp Bales,
PRL(17), No. 4, April 4 1996, pp. 413-419. 9605
BibRef

Revow, M., Williams, C.K.I., Hinton, G.E.,
Using Generative Models for Handwritten Digit Recognition,
PAMI(18), No. 6, June 1996, pp. 592-606.
IEEE DOI 9607
BibRef

Hinton, G.E., Dayan, P., Revow, M.,
Modeling the Manifolds of Images of Handwritten Digits,
TNN(8), No. 1, January 1997, pp. 65-74. 9701
BibRef

Mayraz, G.[Guy], Hinton, G.E.[Geoffrey E.],
Recognizing Handwritten Digits Using Hierarchical Products of Experts,
PAMI(24), No. 2, February 2002, pp. 189-197.
IEEE DOI 0202
BibRef

Favata, J.T., Srikantan, G.,
A Multiple Feature/Resolution Approach to Handprinted Digit and Character-Recognition,
IJIST(7), No. 4, Winter 1996, pp. 304-311. 9612
BibRef

Gorski, N.D., Gorskaya, L.M.,
Estimation of Prior Probabilities for Numeral Recognition,
PRL(18), No. 1, January 1997, pp. 97-103. 9704
BibRef

Ha, T.M., Bunke, H.,
Off-Line, Handwritten Numeral Recognition by Perturbation Method,
PAMI(19), No. 5, May 1997, pp. 535-539.
IEEE DOI 9705
BibRef

Ha, T.M.,
Efficient detection of abnormalities in large OCR databases,
ICDAR97(1006-1010).
IEEE DOI 9708
BibRef

Ha, T.M., Zimmermann, M., Bunke, H.,
Off-Line Handwritten Numeral String Recognition by Combining Segmentation-Based and Segmentation-Free Methods,
PR(31), No. 3, March 1998, pp. 257-272.
Elsevier DOI 9802
BibRef

Chiang, J.H., Gader, P.D.,
Recognition of Handprinted Numerals in Visa(R) Card Application Forms,
MVA(10), No. 3, 1997, pp. 144-149.
Springer DOI 9709
BibRef

Amit, Y.[Yali], Geman, D.[David], Wilder, K.[Kenneth],
Joint Induction of Shape Features and Tree Classifiers,
PAMI(19), No. 11, November 1997, pp. 1300-1305.
IEEE DOI 9712
Generate description using large family of binary features (every local geometric arrangement). Apply to NIST dataset. BibRef

Jain, A.K.[Anil K.], Zongker, D.[Douglas],
Representation and Recognition of Handwritten Digits Using Deformable Templates,
PAMI(19), No. 12, December 1997, pp. 1386-1390.
IEEE DOI 9712
Template Matching. BibRef

Hamamoto, Y., Uchimura, S., Watanabe, M., Yasuda, T., Mitani, Y., Tomita, S.,
A Gabor Filter Based Method for Recognizing Handwritten Numerals,
PR(31), No. 4, April 1998, pp. 395-400.
Elsevier DOI 9803
BibRef

Watanabe, M., Hamamoto, Y., Yasuda, T., Tomita, S.,
Normalization techniques of handwritten numerals for Gabor filters,
ICDAR97(303-307).
IEEE DOI 9708
BibRef

Hamamoto, Y., Uchimura, S., Watanabe, M., Yasuda, T., Tomita, S.,
Recognition of Handwritten Numerals Using Gabor Features,
ICPR96(III: 250-253).
IEEE DOI 9608
(Yamaguchi Univ., J) BibRef

Reddy, N.V.S., Nagabhushan, P.,
A Connectionist Expert System Model for Conflict Resolution in Unconstrained Handwritten Numeral Recognition,
PRL(19), No. 2, February 1998, pp. 161-169. 9808
BibRef

Kim, D.J.[Dai-Jin], Bang, S.Y.[Sung-Yang],
A Handwriting Numeral Character Classification Using Tolerant Rough Set,
PAMI(22), No. 9, September 2000, pp. 923-937.
IEEE DOI 0010
BibRef

Lu, Y., Schlosser, S., Janeczko, M.,
Fourier descriptors and handwritten digit recognition,
MVA(6), No. 1, 1993, pp. 25-34. BibRef 9300

Lou, Z., Liu, K., Yang, J.Y., Suen, C.Y.,
Rejection Criteria and Pairwise Discrimination of Handwritten Numerals Based on Structural Features,
PAA(2), No. 3, 1999, pp. 228-238. BibRef 9900

Chen, Y.K.[Yi-Kai], Wang, J.F.[Jhing-Fa],
Segmentation of Single- or Multiple-Touching Handwritten Numeral String Using Background and Foreground Analysis,
PAMI(22), No. 11, November 2000, pp. 1304-1317.
IEEE DOI 0012
BibRef
Earlier:
Segmentation of Handwritten Connected Numeral String Using Background and Foreground Analysis,
ICPR00(Vol II: 598-601).
IEEE DOI 0009
Skeleton approach. BibRef

Portegys, T.E.[Thomas E.],
Recognizing Hand-Printed Digits with a Distance Quasi-Metric,
CVIU(80), No. 3, December 2000, pp. 289-294.
DOI Link 0012
BibRef

Saradhi, V.V.[V. Vijaya], Murty, M.N.[M. Narasimha],
Bootstrapping for efficient handwritten digit recognition,
PR(34), No. 5, May 2001, pp. 1047-1056.
Elsevier DOI 0102
BibRef

Kim, K.K.[Kye Kyung], Kim, J.H.[Jin Ho], Suen, C.Y.[Ching Y.],
Segmentation-based recognition of handwritten touching pairs of digits using structural features,
PRL(23), No. 1-3, January 2002, pp. 13-24.
Elsevier DOI 0201
BibRef

Ping, Z.[Zhang], Lihui, C.[Chen],
A novel feature extraction method and hybrid tree classification for handwritten numeral recognition,
PRL(23), No. 1-3, January 2002, pp. 45-56.
Elsevier DOI 0201
BibRef

Kim, H.C.[Hyun-Chul], Kim, D.J.[Dai-Jin], Bang, S.Y.[Sung Yang],
A numeral character recognition using the PCA mixture model,
PRL(23), No. 1-3, January 2002, pp. 103-111.
Elsevier DOI 0201

See also Face recognition using the mixture-of-eigenfaces method. BibRef

Shi, M.[Meng], Fujisawa, Y.[Yoshiharu], Wakabayashi, T.[Tetsushi], Kimura, F.[Fumitaka],
Handwritten numeral recognition using gradient and curvature of gray scale image,
PR(35), No. 10, October 2002, pp. 2051-2059.
Elsevier DOI 0206
BibRef

Shi, M.[Meng], Ohyama, W.[Wataru], Wakabayashi, T., Kimura, F.,
Clustering with projection distance and pseudo Bayes discriminant function for handwritten numeral recognition,
ICDAR01(1007-1011).
IEEE DOI 0109
BibRef

Wakabayashi, T., Shi, M., Ohyama, W., Kimura, F.,
Accuracy improvement of handwritten numeral recognition by mirror image learning,
ICDAR01(338-343).
IEEE DOI 0109
BibRef

Teow, L.N.[Loo-Nin], Loe, K.F.[Kia-Fock],
Robust vision-based features and classification schemes for off-line handwritten digit recognition,
PR(35), No. 11, November 2002, pp. 2355-2364.
Elsevier DOI 0208
BibRef
Earlier:
Handwritten Digit Recognition with a Novel Vision Model that Extracts Linearly Separable Features,
CVPR00(II: 76-81).
IEEE DOI 0005
BibRef

Chen, G.Y., Bui, T.D., Krzyzak, A.,
Contour-based handwritten numeral recognition using multiwavelets and neural networks,
PR(36), No. 7, July 2003, pp. 1597-1604.
Elsevier DOI 0304
BibRef

Chen, G.Y., Bui, T.D., Krzyzak, A.,
Rotation invariant pattern recognition using ridgelets, wavelet cycle-spinning and Fourier features,
PR(38), No. 12, December 2005, pp. 2314-2322.
Elsevier DOI 0510
BibRef

Yang, L.H.[Li-Hua], Suen, C.Y.[Ching Y.], Bui, T.D.[Tien D.], Zhang, P.[Ping],
Discrimination of similar handwritten numerals based on invariant curvature features,
PR(38), No. 7, July 2005, pp. 947-963.
Elsevier DOI 0505
BibRef

Zhang, P., Bui, T.D., Suen, C.Y.,
Hybrid feature extraction and feature selection for improving recognition accuracy of handwritten numerals,
ICDAR05(I: 136-140).
IEEE DOI 0508
BibRef
Earlier: A1, A3, A2:
Multi-modal nonlinear feature reduction for the recognition of handwritten numerals,
CRV04(393-400).
IEEE DOI 0408
BibRef

Bellili, A., Gilloux, M., Gallinari, P.,
An MLP-SVM combination architecture for offline handwritten digit recognition: Reduction of recognition errors by Support Vector Machines rejection mechanisms,
IJDAR(5), No. 4, July 2003, pp. 244-252.
Springer DOI 0308
BibRef
Earlier:
An hybrid MLP-SVM handwritten digit recognizer,
ICDAR01(28-32).
IEEE DOI 0109
BibRef

Goltsev, A.[Alexander], Rachkovskij, D.[Dmitri],
Combination of the assembly neural network with a perceptron for recognition of handwritten digits arranged in numeral strings,
PR(38), No. 3, March 2005, pp. 315-322.
Elsevier DOI 0412
BibRef

Parkins, A.D., Nandi, A.K.,
Method for calculating first-order derivative based feature saliency information in a trained neural network and its application to handwritten digit recognition,
VISP(152), No. 2, April 2005, pp. 137-147.
DOI Link 0510
BibRef

Sung, J.M.[Jae-Mo], Bang, S.Y.[Sung-Yang], Choi, S.J.[Seung-Jin],
A Bayesian network classifier and hierarchical Gabor features for handwritten numeral recognition,
PRL(27), No. 1, 1 January 2006, pp. 66-75.
Elsevier DOI 0512
BibRef

Sung, J.M.[Jae-Mo], Ghahramani, Z.[Zoubin], Bang, S.Y.[Sung-Yang],
Latent-Space Variational Bayes,
PAMI(30), No. 12, December 2008, pp. 2236-2242.
IEEE DOI 0811
BibRef

Sung, J.M.[Jae-Mo], Bang, S.Y.[Sung-Yang],
Hierarchical Bayesian Network for Handwritten Digit Recognition,
CVS03(396 ff).
Springer DOI 0306
BibRef

Savas, B.[Berkant], Eldén, L.[Lars],
Handwritten digit classification using higher order singular value decomposition,
PR(40), No. 3, March 2007, pp. 993-1003.
Elsevier DOI 0611
Tensors; Higher order singular value decomposition; Tensor approximation; Least squares BibRef

Hoffmann, H.[Heiko],
Kernel PCA for novelty detection,
PR(40), No. 3, March 2007, pp. 863-874.
Elsevier DOI 0611
Kernel method; Novelty detection; PCA; Handwritten digit; Breast cancer BibRef

Suresh, R.M., Arumugam, S.,
Fuzzy technique based recognition of handwritten characters,
IVC(25), No. 2, February 2007, pp. 230-239.
Elsevier DOI 0701
Fuzzy logic; Fuzzy context-free grammar; Preprocessing; Polygonal approximation; Segmentation; Labeling; Handwritten numerals; Modified parsing algorithm BibRef

Lauer, F.[Fabien], Suen, C.Y.[Ching Y.], Bloch, G.[Gerard],
A trainable feature extractor for handwritten digit recognition,
PR(40), No. 6, June 2007, pp. 1816-1824.
Elsevier DOI 0704
Character recognition; Support vector machines; Convolutional neural networks; Feature extraction; Elastic distortion BibRef

Hanmandlu, M.[Madasu], Murthy, O.V.R.[O.V. Ramana],
Fuzzy model based recognition of handwritten numerals,
PR(40), No. 6, June 2007, pp. 1840-1854.
Elsevier DOI 0704
Box approach; Fuzzy sets; Membership function; Structural parameters; Entropy BibRef

Hanmandlu, M.[Madasu], Yusof, M.H.M.[Mohammad Hafizuddin Mohd], Madasu, V.K.[Vamsi Krishna],
Fuzzy Modeling Based Recognition of Multi-font Numerals,
DAGM03(204-211).
Springer DOI 0310
BibRef

Zhang, P.[Ping], Bui, T.D.[Tien D.], Suen, C.Y.[Ching Y.],
A novel cascade ensemble classifier system with a high recognition performance on handwritten digits,
PR(40), No. 12, December 2007, pp. 3415-3429.
Elsevier DOI 0709
Handwritten digit recognition; Hybrid feature extraction; Cascade classifier system; Rejection criteria; Ensemble classifier; Gating networks; Neural networks; Genetic algorithms BibRef

Zhou, J.[Jie], Peng, H.[Hanchuan], Suen, C.Y.[Ching Y.],
Data-driven decomposition for multi-class classification,
PR(41), No. 1, January 2008, pp. 67-76.
Elsevier DOI 0710
Multi-class classification; Error Correcting Output Coding (ECOC); Data-driven Error Correcting Output Coding (DECOC); Support vector machine; Handwritten numeral recognition; Gene expression classification BibRef

Kherallah, M.[Monji], Haddad, L.[Lobna], Alimi, A.M.[Adel M.], Mitiche, A.[Amar],
On-line handwritten digit recognition based on trajectory and velocity modeling,
PRL(29), No. 5, 1 April 2008, pp. 580-594.
Elsevier DOI 0802
Handwriting modeling; Stroke overlapping; Elliptic trajectory modeling; Beta velocity modeling; Digit recognition BibRef

Vellasques, E., Oliveira, L.S., de Souza Britto, Jr., A.[Alceu], Koerich, A.L., Sabourin, R.,
Filtering segmentation cuts for digit string recognition,
PR(41), No. 10, October 2008, pp. 3044-3053.
Elsevier DOI 0808
Segmentation; Filtering BibRef

Ko, A.H.R.[Albert Hung-Ren], Cavalin, P.R.[Paulo Rodrigo], Sabourin, Jr., R.[Robert], de Souza Britto, Jr., A.[Alceu],
Leave-One-Out-Training and Leave-One-Out-Testing Hidden Markov Models for a Handwritten Numeral Recognizer: The Implications of a Single Classifier and Multiple Classifications,
PAMI(31), No. 12, December 2009, pp. 2168-2178.
IEEE DOI 0911
Generally HMM have a problem with noise. Improves recognition from 98% to 98.88%
See also Evaluation of incremental learning algorithms for HMM in the recognition of alphanumeric characters. BibRef

Oliveira, L.S., de Souza Britto, Jr., A.[Alceu], Sabourin, R.,
A synthetic database to assess segmentation algorithms,
ICDAR05(I: 207-211).
IEEE DOI 0508
BibRef

Ng, G.S.[Geok See], Erdogan, S.[Sevki], Shi, D.M.[Da-Ming], Wahab, A.[Abdul],
Insight Of Fuzzy Neural Systems In The Application Of Handwritten Digits Classification,
IJIG(6), No. 4, October 2006, pp. 511-532. 0610
BibRef

Abdel Azeem, S.[Sherif], El-Sherif, E.[Ezzat],
Arabic handwritten digit recognition,
IJDAR(11), No. 3, December 2008, pp. xx-yy.
Springer DOI 0804
BibRef

Lian, H.[Heng],
Bayesian Nonlinear Principal Component Analysis Using Random Fields,
PAMI(31), No. 4, April 2009, pp. 749-754.
IEEE DOI 0903
Efficient computation. PCA for digit recognition. BibRef

Cavalin, P.R.[Paulo R.], Sabourin, R.[Robert], Suen, C.Y.[Ching Y.], de Souza Britto, Jr., A.[Alceu],
Evaluation of incremental learning algorithms for HMM in the recognition of alphanumeric characters,
PR(42), No. 12, December 2009, pp. 3241-3253.
Elsevier DOI 0909
Incremental learning; Hidden Markov models; Ensembles of classifiers; Handwriting recognition; Isolated digits; Uppercase letters
See also Leave-One-Out-Training and Leave-One-Out-Testing Hidden Markov Models for a Handwritten Numeral Recognizer: The Implications of a Single Classifier and Multiple Classifications. BibRef

Hamidi, M.[Mandana], Borji, A.[Ali],
Invariance analysis of modified C2 features: case study: Handwritten digit recognition,
MVA(21), No. 6, October 2010, pp. 969-979.
WWW Link. 1011
BibRef

He, C.L.[Chun Lei], Lam, L.[Louisa], Suen, C.Y.[Ching Y.],
Rejection measurement based on linear discriminant analysis for document recognition,
IJDAR(14), No. 3, September 2011, pp. 263-272.
WWW Link. 1109
BibRef
Earlier:
A Novel Rejection Measurement in Handwritten Numeral Recognition Based on Linear Discriminant Analysis,
ICDAR09(451-455).
IEEE DOI 0907
BibRef

He, C.L.[Chun Lei], Lam, L.[Louisa], Suen, C.Y.[Ching Y.],
Automatic Discrimination between Confusing Classes with Writing Styles Verification in Arabic Handwritten Numeral Recognition,
ICPR10(2045-2048).
IEEE DOI 1008
BibRef

He, C.L.[Chun Lei], Suen, C.Y.[Ching Y.],
Error Reduction Based on Error Categorization in Arabic Handwritten Numeral Recognition,
FHR10(463-468).
IEEE DOI 1011
BibRef

Niu, X.X.[Xiao-Xiao], Suen, C.Y.[Ching Y.],
A novel hybrid CNN-SVM classifier for recognizing handwritten digits,
PR(45), No. 4, April 2012, pp. 1318-1325.
Elsevier DOI 1112
Hybrid model; Convolutional Neural Network; Support Vector Machine; Handwritten digit recognition BibRef

Deselaers, T.[Thomas], Gass, T.[Tobias], Heigold, G.[Georg], Ney, H.[Hermann],
Latent Log-Linear Models for Handwritten Digit Classification,
PAMI(34), No. 6, June 2012, pp. 1105-1117.
IEEE DOI 1205
BibRef
Earlier: A2, A1, A4, Only:
Deformation-Aware Log-Linear Models,
DAGM09(201-210).
Springer DOI 0909
Exented log-linear model with latent variables. Image deformation aware models. BibRef

Bernard, S.[Simon], Adam, S.[Sébastien], Heutte, L.[Laurent],
Dynamic Random Forests,
PRL(33), No. 12, 1 September 2012, pp. 1580-1586.
Elsevier DOI 1208
BibRef
Earlier:
Using Random Forests for Handwritten Digit Recognition,
ICDAR07(1043-1047).
IEEE DOI 0709
Random forests; Ensemble of classifiers; Random feature selection; Dynamic induction BibRef

Pirlo, G.[Giuseppe], Impedovo, S.[Sebastiano],
Adaptive Membership Functions for Handwritten Character Recognition by Voronoi-Based Image Zoning,
IP(21), No. 9, September 2012, pp. 3827-3837.
IEEE DOI 1208
BibRef
Earlier: A2, A1:
Tuning between Exponential Functions and Zones for Membership Functions Selection in Voronoi-Based Zoning for Handwritten Character Recognition,
ICDAR11(997-1001).
IEEE DOI 1111
BibRef

Impedovo, S.[Sebastiano], Pirlo, G.[Giuseppe], Modugno, R.[Raffaele],
New Advancements in Zoning-Based Recognition of Handwritten Characters,
FHR12(665-669).
IEEE DOI 1302
BibRef

Impedovo, S.[Sebastiano], Modugno, R.[Raffaele], Pirlo, G.[Giuseppe],
Analysis of Membership Functions for Voronoi-Based Classification,
FHR10(220-225).
IEEE DOI 1011
BibRef
And:
Membership Functions for Zoning-Based Recognition of Handwritten Digits,
ICPR10(1876-1879).
IEEE DOI 1008
BibRef

Berthiaume, V.[Vincent], Cheriet, M.[Mohamed],
Handwritten Digit Recognition by Fourier-Packet Descriptors,
ELCVIA(11), No. 1, 2012, pp. xx-yy.
DOI Link 1212
BibRef

Salimi, H.[Hamid], Giveki, D.[Davar],
Farsi/Arabic handwritten digit recognition based on ensemble of SVD classifiers and reliable multi-phase PSO combination rule,
IJDAR(16), No. 4, December 2013, pp. 371-386.
WWW Link. 1312
BibRef

Dash, K.S.[Kalyan S], Puhan, N.B., Panda, G.[Ganapati],
Handwritten numeral recognition using non-redundant Stockwell transform and bio-inspired optimal zoning,
IET-IPR(9), No. 10, 2015, pp. 874-882.
DOI Link 1511
BibRef
And:
Gestalt configural superiority effect: A complexity paradigm for handwritten numeral recognition,
ICAPR15(1-6)
IEEE DOI 1511
affine transforms BibRef
And:
On extraction of features for handwritten Odia numeral recognition in transformed domain,
ICAPR15(1-6)
IEEE DOI 1511
error analysis. feature extraction BibRef

Dash, K.S.[Kalyan S], Puhan, N.B., Panda, G.[Ganapati],
BESAC: Binary External Symmetry Axis Constellation for unconstrained handwritten character recognition,
PRL(83, Part 3), No. 1, 2016, pp. 413-422.
Elsevier DOI 1609
External symmetry axis BibRef

Cecotti, H.[Hubert],
Active graph based semi-supervised learning using image matching: Application to handwritten digit recognition,
PRL(73), No. 1, 2016, pp. 76-82.
Elsevier DOI 1604
Active learning BibRef

Hosseinzadeh, H.[Hamidreza], Razzazi, F.[Farbod], Kabir, E.[Ehsanollah],
A weakly supervised large margin domain adaptation method for isolated handwritten digit recognition,
JVCIR(38), No. 1, 2016, pp. 307-315.
Elsevier DOI 1605
BibRef
Earlier: A1, A2, Only:
A writer adaptation method for isolated handwritten digit recognition based on Ensemble Projection of features,
IPRIA15(1-5)
IEEE DOI 1603
Writer adaptation. handwritten character recognition BibRef

Iwana, B.K.[Brian Kenji], Frinken, V.[Volkmar], Riesen, K.[Kaspar], Uchida, S.[Seiichi],
Efficient temporal pattern recognition by means of dissimilarity space embedding with discriminative prototypes,
PR(64), No. 1, 2017, pp. 268-276.
Elsevier DOI 1701
Temporal patterns BibRef

Iwana, B.K.[Brian Kenji], Uchida, S.[Seiichi], Riesen, K.[Kaspar], Frinken, V.[Volkmar],
Tackling temporal pattern recognition by vector space embedding,
ICDAR15(816-820)
IEEE DOI 1511
Input from a electronic pen. BibRef

Dai, B., Li, H., Wei, L.,
Image Processing Unit for General-Purpose Representation and Association System for Recognizing Low-Resolution Digits With Visual Information Variability,
SMCS(48), No. 3, March 2018, pp. 317-328.
IEEE DOI 1802
Image recognition, Iterative decoding, Prototypes, Switches, Visual systems, Visualization, Error correction codes, intelligent systems BibRef

Hochuli, A.G., Oliveira, L.S., de Souza Britto, Jr., A.[Alceu], Sabourin, R.,
Handwritten digit segmentation: Is it still necessary?,
PR(78), 2018, pp. 1-11.
Elsevier DOI 1804
BibRef

Singh, P.K.[Pawan Kumar], Das, S.[Supratim], Sarkar, R.[Ram], Nasipuri, M.[Mita],
Script invariant handwritten digit recognition using a simple feature descriptor,
IJCVR(8), No. 5, 2018, pp. 543-560.
DOI Link 1810
BibRef

Krishnasamy, G.[Ganesh], Paramesran, R.[Raveendran],
Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks,
SP:IC(70), 2019, pp. 68-78.
Elsevier DOI 1812
Feature selection, Semisupervised learning, Multiview learning, Multitask learning, Handwritten digits recognition, 3D motion data analysis BibRef

Pinho, A.J.[Armando J.], Pratas, D.[Diogo],
An Application of Data Compression Models to Handwritten Digit Classification,
ACIVS18(487-495).
Springer DOI 1810
BibRef

Ospina Mosquera, C.M.[Claudia Marcela], Salcedo Parra, O.J.[Octavio José], Espitia R., M.J.[Miguel J.],
Optical Recognition of Numerical Characters in Digital Images of Glucometers,
AMDO18(106-120).
Springer DOI 1807
BibRef

Jain, A.[Ayushi], Subrahmanyam, G.R.K.S.[Gorthi R. K. Sai], Mishra, D.[Deepak],
Stacked Features Based CNN for Rotation Invariant Digit Classification,
PReMI17(527-533).
Springer DOI 1711
BibRef

Lee, S.J., Koo, G., Choi, H., Kim, S.W.,
Transfer learning of a deep convolutional neural network for localizing handwritten slab identification numbers,
MVA17(330-333)
DOI Link 1708
Machine learning, Neural networks, Production facilities, Silicon compounds, Slabs, Training, Training data. BibRef

Ablavatski, A.[Artsiom], Lu, S.J.[Shi-Jian], Cai, J.F.[Jian-Fei],
Enriched Deep Recurrent Visual Attention Model for Multiple Object Recognition,
WACV17(971-978)
IEEE DOI 1609
Characters and digits. Backpropagation, Computational modeling, Computer architecture, Random access memory, Recurrent neural networks, Visualization BibRef

Ashiquzzaman, A., Tushar, A.K.,
Handwritten Arabic numeral recognition using deep learning neural networks,
IVPR17(1-4)
IEEE DOI 1704
Biological neural networks BibRef

Shopon, M., Mohammed, N., Abedin, M.A.,
Image augmentation by blocky artifact in Deep Convolutional Neural Network for handwritten digit recognition,
IVPR17(1-6)
IEEE DOI 1704
Biological neural networks BibRef

Pérez, A.[Andrés], Quevedo, A.[Angélica], Caicedo, J.C.[Juan C.],
Computing Arithmetic Operations on Sequences of Handwritten Digits,
CIARP16(393-400).
Springer DOI 1703
BibRef

Vodianyk, D.[Dmytro], Rokita, P.[Przemyslaw],
Evolving Node Transfer Functions in Artificial Neural Networks for Handwritten Digits Recognition,
ICCVG16(604-613).
Springer DOI 1611
BibRef

Xu, X.F.[Xiao-Fan], Corrigan, D.[David], Dehghani, A.[Alireza], Caulfield, S.[Sam], Moloney, D.[David],
3D Object Recognition Based on Volumetric Representation Using Convolutional Neural Networks,
AMDO16(147-156).
Springer DOI 1608
volumetric representation of 3D digits BibRef

Nagar, R., Mitra, S.K.,
Feature extraction based on stroke orientation estimation technique for handwritten numeral,
ICAPR15(1-6)
IEEE DOI 1511
feature extraction BibRef

Barbuzzi, D., Pirlo, G., Uchida, S., Frinken, V., Impedovo, D.,
Similarity-based regularization for semi-supervised learning for handwritten digit recognition,
ICDAR15(101-105)
IEEE DOI 1511
Feedback-based Strategies BibRef

Wicht, B.[Baptiste], Henneberty, J.[Jean],
Mixed handwritten and printed digit recognition in Sudoku with Convolutional Deep Belief Network,
ICDAR15(861-865)
IEEE DOI 1511
Camera-based OCR BibRef

Pan, S.L.[Shu-Lan], Wang, Y.W.[Yan-Wei], Liu, C.S.[Chang-Song], Ding, X.Q.[Xiao-Qing],
A discriminative cascade CNN model for offline handwritten digit recognition,
MVA15(501-504)
IEEE DOI 1507
Distortion BibRef

Nguyen, T.V.[Toan Van], Sae-Bae, N.[Napa], Memon, N.[Nasir],
Finger-drawn pin authentication on touch devices,
ICIP14(5002-5006)
IEEE DOI 1502
Authentication BibRef

Saavedra, J.M.[Jose M.],
Handwritten Digit Recognition Based on Pooling SVM-Classifiers Using Orientation and Concavity Based Features,
CIARP14(658-665).
Springer DOI 1411
BibRef

Gil, A.M.[Adriano Mendes], Fernandes Costa Filho, C.F.[Cícero Ferreira], Fernandes Costa, M.G.[Marly Guimarães],
Handwritten Digit Recognition Using SVM Binary Classifiers and Unbalanced Decision Trees,
ICIAR14(I: 246-255).
Springer DOI 1410
BibRef

Ghifary, M., Kleijn, W.B., Zhang, M.J.[Meng-Jie],
Sparse representations in deep learning for noise-robust digit classification,
IVCNZ13(340-345)
IEEE DOI 1402
Boltzmann machines BibRef

Impedovo, S., Mangini, F.M., Pirlo, G., Barbuzzi, D., Impedovo, D.,
Voronoi Tessellation for Effective and Efficient Handwritten Digit Classification,
ICDAR13(435-439)
IEEE DOI 1312
computational geometry BibRef

Diem, M., Fiel, S., Garz, A., Keglevic, M., Kleber, F., Sablatnig, R.,
ICDAR 2013 Competition on Handwritten Digit Recognition (HDRC 2013),
ICDAR13(1422-1427)
IEEE DOI 1312
handwritten character recognition BibRef

Le, H.M.[Hieu M.], Duong, A.T.[An T.], Tran, S.T.[Son T.],
Multiple-Classifier Fusion Using Spatial Features for Partially Occluded Handwritten Digit Recognition,
ICIAR13(124-132).
Springer DOI 1307
BibRef

Sermanet, P.[Pierre], Chintala, S.[Soumith], Le Cun, Y.L.[Yann L.],
Convolutional neural networks applied to house numbers digit classification,
ICPR12(3288-3291).
WWW Link. 1302
BibRef

Yu, X.G.[Xin-Guo],
Localization and extraction of the four clock-digits using the knowledge of the digital video clock,
ICPR12(1217-1220).
WWW Link. 1302
Not handwritten BibRef

Barbuzzi, D.[Donato], Impedovo, D.[Donato],
Learning Iterative Strategies in Multi-Expert Systems Using SVMs for Digit Recognition,
CIAP13(I:121-130).
Springer DOI 1311
BibRef

Barbuzzi, D.[Donato], Impedovo, D.[Donato], Pirlo, G.,
Benchmarking of Update Learning Strategies on Digit Classifier Systems,
FHR12(35-40).
IEEE DOI 1302
BibRef

Impedovo, S., Mangini, F.M.,
A Novel Technique for Handwritten Digit Classification Using Genetic Clustering,
FHR12(236-240).
IEEE DOI 1302
BibRef

Abbas, N.[Nassim], Chibani, Y.[Youcef], Nemmour, H.[Hassiba],
Handwritten Digit Recognition Based on a DSmT-SVM Parallel Combination,
FHR12(241-246).
IEEE DOI 1302
BibRef

Azeem, S.A.[Sherif Abdel], El Meseery, M.[Maha], Ahmed, H.[Hany],
Online Arabic Handwritten Digits Recognition,
FHR12(135-140).
IEEE DOI 1302
BibRef

Bull, G., Gao, J.B.[Jun-Bin],
Classification of Hand-Written Digits Using Chordiograms,
DICTA11(358-363).
IEEE DOI 1205
BibRef

Wang, Z.[Zhe], Huang, Y.P.[Ya-Ping], Luo, S.W.[Si-Wei], Wang, L.[Liang],
A biologically inspired system for fast handwritten digit recognition,
ICIP11(1749-1752).
IEEE DOI 1201
BibRef

de Santana Pereira, C.[Cristiano], Cavalcanti, G.D.C.[George D.C.],
Handwritten connected digits detection: An approach using instance selection,
ICIP11(2613-2616).
IEEE DOI 1201
BibRef

Li, P.[Peng], Li, R.[Rui],
The research on arabic numeral symbol's use in poster design,
IASP11(67-70).
IEEE DOI 1112
Not recognition, but history. BibRef

Gimenez, A.[Adria], Andres-Ferrer, J., Juan, A.[Alfons], Serrano, N.[Nicolás],
Discriminative Bernoulli Mixture Models for Handwritten Digit Recognition,
ICDAR11(558-562).
IEEE DOI 1111
BibRef

Mizukami, Y.[Yoshiki], Tadamura, K.[Katsumi], Warrell, J.[Jonathan], Li, P.[Peng], Prince, S.J.D.[Simon J.D.],
CUDA Implementation of Deformable Pattern Recognition and its Application to MNIST Handwritten Digit Database,
ICPR10(2001-2004).
IEEE DOI 1008
BibRef

Lawal, I.A.[Isah A.], Abdel-Aal, R.E.[Radwan E.], Mahmoud, S.A.[Sabri A.],
Recognition of Handwritten Arabic (Indian) Numerals Using Freeman's Chain Codes and Abductive Network Classifiers,
ICPR10(1884-1887).
IEEE DOI 1008
BibRef

Bulacu, M.[Marius], Brink, A.A.[Axel A.], van der Zant, T.[Tijn], Schomaker, L.R.B.[Lambert R.B.],
Recognition of Handwritten Numerical Fields in a Large Single-Writer Historical Collection,
ICDAR09(808-812).
IEEE DOI 0907
BibRef

Seijas, L.M.[Leticia M.], Segura, E.C.[Enrique C.],
A Wavelet-Based Descriptor for Handwritten Numeral Classification,
FHR12(653-658).
IEEE DOI 1302
BibRef
Earlier:
Detection of Ambiguous Patterns Using SVMs: Application to Handwritten Numeral Recognition,
CAIP09(840-847).
Springer DOI 0909
BibRef

Romero, D.[Diego], Ruedin, A.[Ana], Seijas, L.[Leticia],
Wavelet-Based Feature Extraction for Handwritten Numerals,
CIAP09(374-383).
Springer DOI 0909
BibRef

Alamri, H.[Huda], He, C.L.[Chun Lei], Suen, C.Y.[Ching Y.],
A New Approach for Segmentation and Recognition of Arabic Handwritten Touching Numeral Pairs,
CAIP09(165-172).
Springer DOI 0909
BibRef

Yu, X.G.[Xin-Guo], Li, Y.Q.[Yi-Qun], Lee, W.S.[Wei San],
Robust time recognition of video clock based on digit transition detection and digit-sequence recognition,
ICPR08(1-4).
IEEE DOI 0812
BibRef

López-Leyva, L.O.[Luis Octavio], Yáñez-Márquez, C.[Cornelio], Flores-Carapia, R.[Rolando], Camacho-Nieto, O.[Oscar],
Handwritten Digit Classification Based on Alpha-Beta Associative Model,
CIARP08(437-444).
Springer DOI 0809
BibRef

Yektaii, M.[Mahdi], Bhattacharya, P.[Prabir],
Cumulative Global Distance for Dimension Reduction in Handwritten Digits Database,
Visual07(216-222).
Springer DOI 0706
BibRef

Huang, K.Z.[Kai-Zhu], Sun, J.[Jun], Hotta, Y.[Yoshinobu], Fujimoto, K.[Katsuhito], Naoi, S.[Satoshi],
An SVM-Based High-accurate Recognition Approach for Handwritten Numerals by Using Difference Features,
ICDAR07(589-593).
IEEE DOI 0709
BibRef

Chen, X.F.[Xue-Feng], Liu, X.B.[Xia-Bi], Jia, Y.D.[Yun-De],
Unsupervised Selection and Discriminative Estimation of Orthogonal Gaussian Mixture Models for Handwritten Digit Recognition,
ICDAR09(1151-1155).
IEEE DOI 0907
BibRef
Earlier:
Learning Handwritten Digit Recognition by the Max-Min Posterior Pseudo-Probabilities Method,
ICDAR07(342-346).
IEEE DOI 0709
BibRef

Hotta, S.,
Transform-Invariance in Local Averaging Classifier for Handwritten Digit Pattern Recognition,
ICDAR07(347-351).
IEEE DOI 0709
BibRef

Zheng, L.H.[Li-Hong], He, X.J.[Xiang-Jian], Wu, Q.A.[Qi-Ang], Hintz, T.,
Learning-Based Number Recognition on Spiral Architecture,
ICARCV06(1-5).
IEEE DOI 0612
BibRef

Zhang, X.L.[Xiao-Li], Nagy, G.[George],
Style Quantification of Scanned Multi-source Digits,
ICPR06(II: 1018-10121).
IEEE DOI 0609
BibRef

Duong, J., Emptoz, H.,
Cascade classifier: design and application to digit recognition,
ICDAR05(II: 1065-1069).
IEEE DOI 0508
BibRef

Cecotti, H., Belaid, A.,
Rejection strategy for convolutional neural network by adaptive topology applied to handwritten digits recognition,
ICDAR05(II: 765-769).
IEEE DOI 0508

See also Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces. BibRef

Fan, X.D.[Xiao-Dong],
Efficient Multiclass Object Detection by a Hierarchy of Classifiers,
CVPR05(I: 716-723).
IEEE DOI 0507
Rather than multiple classifiers, 1 per object class, a hierarchical approach. Detection of digits. BibRef

Ng, G.S., Murali, T., Wahab, A., Sriskanthan, N.,
Classification of handwritten digits using evolving fuzzy neural network,
ICARCV04(II: 1410-1415).
IEEE DOI 0412
BibRef

Miller, E.G.[Erik G.], Chef d'hotel, C.[Christophe],
Practical non-parametric density estimation on a transformation group for vision,
CVPR03(II: 114-121).
IEEE DOI 0307
propose a suitable invariant estimator on the linear group of non-singular matrices with positive determinant. Apply to digit recognition. BibRef

Yamaguchi, T., Nakano, Y., Maruyama, M., Miyao, H., Hananoi, T.,
Digit classification on signboards for telephone number recognition,
ICDAR03(359-363).
IEEE DOI 0311
BibRef

Valveny, E., Lopez, A.,
Numeral recognition for quality control of surgical sachets,
ICDAR03(379-383).
IEEE DOI 0311
BibRef

Muramatsu, H., Kobayashi, T., Sugiyama, T., Abe, K.,
Improvement of matching and evaluation in handwritten numeral recognition using flexible standard patterns,
ICDAR03(273-277).
IEEE DOI 0311
BibRef

Kobayashi, T., Nakamura, K., Muramatsu, H., Sugiyama, T., Abe, K.,
Handwritten numeral recognition using flexible matching based on learning of stroke statistics,
ICDAR01(612-616).
IEEE DOI 0109
BibRef

Takahashi, K., Nishiwaki, D.,
A class-modular GLVQ ensemble with outlier learning for handwritten digit recognition,
ICDAR03(268-272).
IEEE DOI 0311
BibRef

Srihari, S.N., Tomai, C.I., Zhang, B.[Bin], Lee, S.J.[Sang-Jik],
Individuality of numerals,
ICDAR03(1096-1100).
IEEE DOI 0311
BibRef

de Avila, S.[Sandra], Matos, L.[Leonardo], de A. Freitas, C.O.[Cinthia O.], de Carvalho, J.M.[João M.],
Evaluating a Zoning Mechanism and Class-Modular Architecture for Handwritten Characters Recognition,
CIARP07(515-524).
Springer DOI 0711
BibRef

Correia, S.E.N., de Carvalho, J.M., Sabourin, R.,
On the performance of wavelets for handwritten numerals recognition,
ICPR02(III: 127-130).
IEEE DOI 0211
BibRef

Kim, K.K.[Kye Kyung], Chung, Y.K.[Yun Koo], Suen, C.Y.,
Post-processing scheme for improving recognition performance of touching handwritten numeral strings,
ICPR02(III: 327-330).
IEEE DOI 0211
BibRef

de Souza Britto, Jr., A.[Alceu], Sabourin, R., Bortolozzi, F., Suen, C.Y.,
A string length predictor to control the level building of HMMs for handwritten numeral recognition,
ICPR02(IV: 31-34).
IEEE DOI 0211
BibRef

Soares de Oliveira, L.E., Lethelier, E., Bortolozzi, F., Sabourin, R.,
A New Segmentation Approach for Handwritten Digits,
ICPR00(Vol II: 323-326).
IEEE DOI 0009
BibRef

Ayat, N.E., Cheriet, M., Suen, C.Y.,
KMOD: A two-parameter SVM kernel for pattern recognition,
ICPR02(III: 331-334).
IEEE DOI 0211
BibRef
And:
Empirical error based optimization of SVM kernels: Application to digit image recognition,
FHR02(292-297).
IEEE Top Reference. 0209
BibRef

Zhang, R.[Rui], Ding, X.Q.[Xiao-Qing],
Offline Handwritten Numeral Recognition Using Orthogonal Gaussian Mixture Model,
ICIP01(I: 1126-1129).
IEEE DOI 0108
BibRef

Zhang, R.[Rui], Ding, X.Q.[Xiao-Qing], Zhang, J.Y.[Jia-Yong],
Offline handwritten character recognition based on discriminative training of orthogonal Gaussian mixture model,
ICDAR01(221-225).
IEEE DOI 0109
BibRef

Ratzlaff, E.H.,
A scanning n-tuple classifier for online recognition of handwritten digits,
ICDAR01(18-22).
IEEE DOI 0109
BibRef

Ye, X.Y.[Xiang-Yun], Cheriet, M., Suen, C.Y.,
A framework of combining numeric string recognizers,
ICDAR01(716-720).
IEEE DOI 0109
BibRef

Ayat, N.E., Cheriet, M., Remaki, L., Suen, C.Y.,
KMOD: a new support vector machine kernel with moderate decreasing for pattern recognition. Application to digit image recognition,
ICDAR01(1215-1219).
IEEE DOI 0109
BibRef

Singh, S., Hewitt, M.,
Cursive Digit and Character Recognition on Cedar Database,
ICPR00(Vol II: 569-572).
IEEE DOI 0009
BibRef

Zhao, B., Liu, Y., Xia, S.W.,
Support Vector Machine and Its Application in Handwritten Numeral Recognition,
ICPR00(Vol II: 720-723).
IEEE DOI 0009
BibRef

Grim, J.[Jiri], Pudil, P., Somol, P.[Petr],
Multivariate Structural Bernoulli Mixtures for Recognition of Handwritten Numerals,
ICPR00(Vol II: 585-589).
IEEE DOI 0009
BibRef

Ping, Z.[Zhang], Lihui, C.[Chen], Kot, A.C.,
A Floating Feature Detector for Handwritten Numeral Recognition,
ICPR00(Vol II: 553-556).
IEEE DOI 0009
BibRef

Nóbrega-Correia, S.E.N., de Carvalho, J.M.[J. Marques],
Optimizing the Recognition Rates of Unconstrained Handwritten Numerals Using Biorthogonal Spline Wavelets,
ICPR00(Vol II: 251-254).
IEEE DOI 0009
BibRef

Mizukami, Y., Sato, T., Tanaka, K.,
Handwritten Digit Recognition by Hierarchical Displacement Extraction with Gradual Prototype Elimination,
ICPR00(Vol II: 339-342).
IEEE DOI 0009
BibRef

Yu, D.,
Analysis and Reconstruction of Broken Handwritten Digits,
ICIP00(Vol II: 700-703).
IEEE DOI 0008
BibRef

Teredesai, A., Govindaraju, V.,
Active digit classifiers: a separability optimization approach to emulate cognition,
ICDAR01(401-405).
IEEE DOI 0109
BibRef

Yoon, S.S.[Sung-Soo], Kim, G.H.[Gyeong-Hwan], Choi, Y.W.[Yeong-Woo], Lee, Y.B.[Yill-Byung],
New paradigm for segmentation and recognition of handwritten numeral string,
ICDAR01(205-209).
IEEE DOI 0109
BibRef

Park, J.[Jaehwa], Govindaraju, V.[Venu],
Active Character Recognition using A*-like Algorithm,
CVPR00(II: 82-87).
IEEE DOI 0005
BibRef

de Coste, D.[Dennis], Burl, M.C.[Michael C.],
Distortion-Invariant Recognition via Jittered Queries,
CVPR00(I: 732-737).
IEEE DOI 0005
BibRef

Plamondon, R.[Rejean], Parizeau, M.[Marc], Li, X.L.[Xiao-Lin],
Model-Based On-Line Handwritten Digit Recognition,
ICPR98(Vol II: 1134-1136).
IEEE DOI 9808
BibRef

Muller, N.[Neil], Herbst, B.M.[Ben M.],
The Use of Eigenpictures for Optical Character Recognition,
ICPR98(Vol II: 1124-1126).
IEEE DOI 9808

See also Building a Representative Training Set Based on Eigenimages. BibRef

Naoi, S., Yabuki, M.,
Global Interpolation Method II for Handwritten Numbers Overlapping a Border by Automatic Knowledge Acquisition of Overlapped Conditions,
ICDAR97(540-543).
IEEE DOI 9708
BibRef

Naoi, S., Hotta, Y., Yabuki, M., Asakawa, A.,
Global interpolation in the segmentation of handwritten characters overlapping a border,
ICIP94(I: 149-153).
IEEE DOI 9411
BibRef

Zhou, J., Suen, C.Y.,
Unconstrained numeral pair recognition using enhanced error correcting output coding: a holistic approach,
ICDAR05(I: 484-488).
IEEE DOI 0508
BibRef

Zhou, J., Gan, Q., Suen, C.Y.,
A High Performance Hand-Printed Numeral Recognition System with Verification Module,
ICDAR97(293-297).
IEEE DOI 9708
BibRef

Shi, Z., Srihari, S.N., Shin, Y.C., Ramanaprasad, V.,
A System for Segmentation and Recognition of Totally Unconstrained Handwritten Numeral Strings,
ICDAR97(455-458).
IEEE DOI 9708
BibRef

Yamauchi, T., Itamoto, Y., Tsukumo, J.,
Shape Based Learning for a Multi-Template Method, and Its Application to Handprinted Numeral Recognition,
ICDAR97(495-498).
IEEE DOI 9708
BibRef

Zhao, B., Su, H., Xia, S.W.,
A New Method For Segmenting Unconstrained Handwritten Numeral String,
ICDAR97(524-527).
IEEE DOI 9708
BibRef

Kim, W., Paik, J., Lee, K., Lee, Y.,
Handwritten Digit Verifier for Improving Recognition Error,
ICDAR97(Tu-3A) 9708
In program, not in proceedings. BibRef

Plamondon, R., Bourdeau, M.,
Validation of Preprocessing Algorithms: A Methodology and Its Application to the Design of a Thinning Algorithm for Handwritten Characters,
ICDAR93(262-269). BibRef 9300

Hotta, Y., Takebe, H., Suwa, M., Naoi, S.,
Accuracy improvement for handwritten Japanese word recognition by combination of character and word recognizer,
ICDAR05(II: 685-689).
IEEE DOI 0508
BibRef

Hotta, Y., Naoi, S., and Suwa, M.,
Handwritten Numeral Recognition Using Personal Handwriting Characteristics Based on Clustering Method,
WACV96(284-289).
IEEE DOI 9609
BibRef

Kawatani, T., Shimizu, H., McEachern, M.,
Handwritten Numeral Recognition with the Improved LDA Method,
ICPR96(IV: 441-446).
IEEE DOI 9608
(Hewlett-Packard Lab. Japan, J) BibRef

Shirali-Shahreza, M.H., Faez, K., Khotanzad, A.,
Recognition of handwritten Persian/Arabic numerals by shadow coding and an edited probabilistic neural network,
ICIP95(III: 436-439).
IEEE DOI 9510
BibRef

Pan, F.[Feng], Keane, M.,
A new set of moment invariants for handwritten numeral recognition,
ICIP94(I: 154-158).
IEEE DOI 9411
BibRef

Bertille, J.M.,
An Elastic Matching Approach Applied to Digit Recognition,
ICDAR93(82-85). BibRef 9300

Fontaine, T., and Shastri, L.,
Handprinted Digit Recognition Using Spatiotemporal Connectionist Models,
CVPR92(169-175).
IEEE DOI Error rate of 1% with 14.6% rejected. BibRef 9200

Li, X.P.[Xue-Ping],
Recognition of connected numeral strings using partial boundary features,
ICPR92(II:677-680).
IEEE DOI 9208
BibRef

Kovacs-Vajna, Z.M., Guerrieri, R., Baccarani, G.,
A novel metric for nearest-neighbor classification of hand-written digits,
ICPR92(II:96-100).
IEEE DOI 9208
BibRef

Schaeken, B., Verschueren, W., Rene de Cotret, Y., Hermanne, A.,
A Hierarchical System for Handwritten Numeral Recognition,
ICPR84(623-625). BibRef 8400

Verschueren, W., Schaeken, B., Rene de Cotret, Y., Hermanne, A.,
Structural Recognition of Handwritten Numerals,
ICPR84(760-762). BibRef 8400

Tang, G.Y., Tzeng, P.S., Hau, C.C.,
A Microcomputer System to Recognize Handwritten Numerals Using a Syntactic-Statistic Approach,
ICPR84(1061-1064). BibRef 8400

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Multiple Classifiers Applied to Arabic Numbers .


Last update:Mar 16, 2024 at 20:36:19