25.4.6.2 Handwritten Characters, Roman, Latin Alphabet

Kuhl, F.,
Classification and Recognition of Hand-Printed Characters,
IEE Natl. ConventionMarch 1963, pp. 75-93. BibRef 6303

Munson, J.H.,
Experiments in the Recognition of Handprinted Text: Part I Character Recognition,
FJCC68(1125-1138). BibRef 6800

Toussaint, G.T., and Donaldson, R.W.,
Algorithms for Recognizing Contour-Traced Handprinted Characters,
TC(19), 1970, pp. 541-546. BibRef 7000

Donaldson, R.W., and Toussaint, G.T.,
Use of Contextual Constraints in Recognition of Contour-Traced handprinted Characters,
TC(20), No. 8, August 1971, pp. 1096. BibRef 7108

Hussain, A.B.S., Toussaint, G.T., and Donaldson, R.W.,
Results Obtained Using a Simple Character Recognition Procedure on Munson's Handprinted Data,
TC(21), 1972, pp. 269-281. BibRef 7200

Casey, R.G.,
Moment Normalization of Handprinted Characters,
IBMRD(14), No. 5, September 1970, pp. 548-557. BibRef 7009

Narasimhan, R., Reddy, V.S.N.,
A syntax-aided recognition scheme for handprinted English letters,
PR(3), No. 4, November 1971, pp. 345-361.
Elsevier DOI 0309
BibRef

Dutta, A.K.,
An Experimental Procedure for Handwritten Character Recognition,
TC(23), 1974, pp. 536-545. BibRef 7400

Lin, W.L., Scully, T.L.,
Computer Identification of Constrained Handprinted Characters with a High Recognition Rate,
SMC(4), 1974, pp. 497-504. BibRef 7400

Dasarathy, B.V., and Kumar, K.S.B.,
CHITRA: Cognitive Handprinted Input Trained Recursively Analyzing System for Recognition of Alphanumeric Characters,
CIS(7), September 1978, No. 3, pp. 253-282. BibRef 7809

Nevins, A.J.[Arthur J.],
An orientation free study of handprinted characters,
PR(11), No. 3, 1979, pp. 155-164.
Elsevier DOI 0309
BibRef

Biswan, P., Majumnder, A.K.,
A Multistage Fuzzy Classifier for Recognition of Handprinted Characters,
SMC(11), 1981, pp. 834-838. BibRef 8100

Fleming, J.F., Hemmings, R.F.,
A Method of Recognition for Handwritten Block Capitals,
PRL(1), 1983, pp. 457-464. BibRef 8300

Mori, S., Yamamoto, K., Yasuda, M.,
Research on Machine Recognition of Handprinted Characters,
PAMI(6), No. 4, July 1984, pp. 386-405. BibRef 8407

Brown, R.M., Fay, T.H., Walker, C.L.,
Handprinted Symbol Recognition System,
PR(21), No. 2, 1988, pp. 91-118.
Elsevier DOI BibRef 8800

Chen, L.H.[Ling-Hwei], Lieh, J.R.[June-Rong],
Handwritten character recognition using a 2-layer random graph model by relaxation matching,
PR(23), No. 11, 1990, pp. 1189-1205.
Elsevier DOI 0401
BibRef

Fukushima, K., and Wake, N.,
Handwritten Alphanumeric Character Recognition by the Neocognitron,
TNN(2), No. 3, 1991, pp. 355-365. BibRef 9100

Kuan, C.C.[Chih-Chau], Hull, J.J.[Jonathan J.], Srihari, S.N.[Sargur N.],
Method and apparatus for handwritten character recognition,
US_Patent5,058,182, October 15, 1991.
WWW Link. BibRef 9110

Blackwell, K.T., Vogl, T.P., Hyman, S.D., Barbour, G.S., Alkon, D.L.,
A new approach to hand-written character recognition,
PR(25), No. 6, June 1992, pp. 655-666.
Elsevier DOI 0401
Neural Network. BibRef

Abe, K.[Keiko],
Character discrimination system employing height-to-width ratio and vertical extraction position information,
US_Patent5,138,668, August 11, 1992.
WWW Link. BibRef 9208

Ohta, J.[Junichi],
Apparatus for converting handwritten characters onto finely shaped characters of common size and pitch, aligned in an inferred direction,
US_Patent5,111,514, May 5, 1992
WWW Link. BibRef 9205

Guo, J., Sun, N., Nemoto, Y., Kimura, M., Echigo, H., Sato, R.,
Recognition of Handwritten Characters Using Pattern Transformation Method with Cosine Function,
IEICE(D-11, J176), No. 4, 1993, pp. 835-842. In Japanese. BibRef 9300

Smith, S.J., Bourgoin, M.O., Sims, K., Voorhees, H.L.,
Handwritten Character Classification Using Nearest-Neighbor in Large Databases,
PAMI(16), No. 9, September 1994, pp. 915-919.
IEEE DOI BibRef 9409

Kovacs-Vajna, Z.M., Guerrieri, R.,
Massively-Parallel Handwritten Character-Recognition Based on the Distance Transform,
PR(28), No. 3, March 1995, pp. 293-301.
Elsevier DOI Distance transform converts binary into gray scale picture. BibRef 9503

Kovacs-Vajna, Z.M.,
A Novel Architecture for High-Quality Hand-Printed Character-Recognition,
PR(28), No. 11, November 1995, pp. 1685-1692.
Elsevier DOI BibRef 9511

Shustorovich, A., Thrasher, C.W.,
Neural-Network Positioning and Classification of Handwritten Characters,
NeurNet(9), No. 4, June 1996, pp. 685-693. 9607
BibRef
Earlier: ICPR96(D82.9). 9608
(Eastman Kodak Company, USA) BibRef

AbuHaiba, I.S.I., Holt, M.J.J., Datta, S.,
Processing of Off-Line Handwritten Text: Polygonal-Approximation and Enforcement of Temporal Information,
GMIP(56), No. 4, July 1994, pp. 324-335. BibRef 9407

Abu Haiba, I.S.I., Holt, M.J.J., Datta, S.,
Straight-Line Approximation and 1D Representation of Off-Line Handwritten Text,
IVC(12), No. 10, December 1994, pp. 649-659.
Elsevier DOI BibRef 9412

Abu Haiba, I.S.I., Datta, S., Holt, M.J.J.,
Fuzzy State Machines to Recognize Totally Unconstructed Handwritten Strokes,
IVC(13), No. 10, December 1995, pp. 755-769.
Elsevier DOI Strokes. BibRef 9512

Abu Haiba, I.S.I., Holt, M.J.J., Datta, S.,
Processing of Binary Images of Handwritten Text Documents,
PR(29), No. 7, July 1996, pp. 1161-1177.
Elsevier DOI 9607
BibRef

Kim, D.H.[Dea-Hwan], Kim, E.J.[Eun-Jung], Bang, S.Y.[Sung-Yang],
A Variation Measure for Handwritten Character Image Data Using Entropy Difference,
PR(30), No. 1, January 1997, pp. 19-29.
Elsevier DOI 9702
Degree of variation. BibRef

Fairhurst, M.C., Rahman, A.F.R.,
Generalized-Approach to the Recognition of Structurally Similar Handwritten Characters Using Multiple Expert Classifiers,
VISP(144), No. 1, February 1997, pp. 15-22. 9706
Classifiers, multiple.
See also New Hybrid Approach in Combining Multiple Experts to Recognize Handwritten Numerals, A.
See also Design Considerations in the Real-Time Implementation of Multiple Expert Image Classifiers within a Modular and Flexible Multiple-platform Design Environment. BibRef

Cheng, D.H., Yan, H.,
Recognition of Broken and Noisy Handwritten Characters Using Statistical-Methods Based on a Broken-Character-Mending Algorithm,
OptEng(36), No. 5, May 1997, pp. 1465-1479. 9706
BibRef

Fan, K.C.[Kuo-Chin], Wang, Y.K.[Yuan-Kai],
A Genetic Sparse Distributed Memory Approach to the Application of Handwritten Character Recognition,
PR(30), No. 12, December 1997, pp. 2015-2022.
Elsevier DOI 9805
Neural net. BibRef

Garris, M.D., Blue, J.L., Candela, G.T., Dimmick, D.L., Geist, J.C., Grother, P.J., Janet, S.A., Omidvar, O.M., Wilson, C.L.,
Design of a Handprint Recognition System,
JEI(6), No. 2, April 1997, pp. 231-243. 9807
BibRef

Garris, M.D., Blue, J.L., Candela, G.T., Dimmick, D.L., Geist, J.C., Grother, P.J., Janet, S.A., Wilson, C.L.,
NIST Form-Based Handprint Recognition System,
NISTIR5469, July 1994. BibRef 9407

Garris, M.D.,
Nist Form-Based Handprint Recognition System (Release 2.2),
NISTIRApril 2003.
HTML Version. Code, OCR. Standard reference form-based handprint recognition system for evaluating optical character recognition. BibRef 0304

Garris, M.D., Blue, J.L., Candela, G.T., Dimmick, D.L., Geist, J.C., Grother, P.J., Janet, S.A., Wilson, C.L.,
Off-line Handwriting Recognition from Forms,
SMC-C95(2783-2788). BibRef 9500

Garris, M.D., Wilson, C.L., Blue, J.L.,
Neural Network Based Systems for Handprint OCR Applications,
IP(7), No. 8, August 1998, pp. 1097-1112.
IEEE DOI 9808
BibRef

Heutte, L., Paquet, T., Moreau, J.V., Lecourtier, Y., Olivier, C.,
A Structural/Statistical Feature Based Vector for Handwritten Character Recognition,
PRL(19), No. 7, May 1998, pp. 629-641. 9808
BibRef
Earlier: A1, A3, A2, A4, A5:
Combining Structural and Statistical Features for the Recognition of Handwritten Characters,
ICPR96(II: 210-214).
IEEE DOI 9608
(Universite de Rouen, F) BibRef

Wada, K., Mori, K., Toraichi, K.,
PARM: A Parallel Relaxation Machine for Handwritten Character Recognition,
PRL(19), No. 5-6, April 1998, pp. 475-481. 9808
BibRef

Chim, Y.C.[Yuen-Chong], Kassim, A.A.[Ashraf A.], Ibrahim, Y.[Yaacob],
Dual Classifier System for Handwritten Alphanumeric Character Recognition,
PAA(1), No. 3, 1998, pp. xx-yy. BibRef 9800

Oh, I.S.[Il-Seok], Suen, C.Y.[Ching Y.],
Distance features for neural network-based recognition of handwritten characters,
IJDAR(1), No. 2, 1998, pp. 319-330. BibRef 9800
Earlier:
A Feature for Character Recognition Based on Directional Distance Distributions,
ICDAR97(288-292).
IEEE DOI 9708
BibRef

Oh, I.S.[Il-Seok], Suen, C.Y.[Ching Y.],
A class-modular feedforward neural network for handwriting recognition,
PR(35), No. 1, January 2002, pp. 229-244.
Elsevier DOI 0111
BibRef

Oh, I.S.[Il-Seok], Lee, J.S.[Jin-Seon], Suen, C.Y.[Ching Y.],
Analysis of Class Separation and Combination of Class-Dependent Features for Handwriting Recognition,
PAMI(21), No. 10, October 1999, pp. 1089-1094.
IEEE DOI BibRef 9910
And:
A class-modularity for character recognition,
ICDAR01(64-68).
IEEE DOI 0109
Feature-Selection-Based combination and class-dependent features. BibRef

Lee, J.S.[Jin-Seon], Suen, C.Y.[Ching Y.], Oh, I.S.[Il-Seok],
Using Class Separation for Feature Analysis and Combination of Class-Dependent Features,
ICPR98(Vol I: 453-455).
IEEE DOI 9808
BibRef

Li, Z.C., Suen, C.Y.,
The partition-combination method for recognition of handwritten characters,
PRL(21), No. 6-7, June 2000, pp. 701-720. 0006
BibRef

Li, Z.C., Suen, C.Y.,
Crucial combinations for the recognition of handwritten letters,
PRL(21), No. 10, October 2000, pp. 873-898. 0008
BibRef

Chen, H., Agazzi, O.E., Suen, C.Y.,
Piecewise Linear Modulation Model of Handwriting,
ICDAR97(363-367).
IEEE DOI 9708
BibRef

Chen, W., Suen, C.Y., Strobel, M.G.,
Extraction of Lines of Texts in Unconstrained Handwritten Documents,
ICDAR97(We-1A) 9708
In program, not in proceedings. BibRef

Ghosh, D., Shivaprasad, A.P.,
An analytic approach for generation of artificial hand-printed character database from given generative models,
PR(32), No. 6, June 1999, pp. 907-920.
Elsevier DOI BibRef 9906

Pessoa, L.F.C.[Lúcio F.C.], Maragos, P.[Petros],
Neural networks with hybrid morphological/rank/linear nodes: a unifying framework with applications to handwritten character recognition,
PR(33), No. 6, June 2000, pp. 945-960.
Elsevier DOI 0004
BibRef

Lazzerini, B.[Beatrice], Marcelloni, F.[Francesco],
A linguistic fuzzy recogniser of off-line handwritten characters,
PRL(21), No. 3, March 2000, pp. 319-327. 0004
BibRef

de Stefano, C., della Cioppa, A., Marcelli, A.,
Character preclassification based on genetic programming,
PRL(23), No. 12, October 2002, pp. 1439-1448.
Elsevier DOI 0206
BibRef

Cilia, N.D.[Nicole Dalia], de Stefano, C.[Claudio], Fontanella, F.[Francesco], di Freca, A.S.[Alessandra Scotto],
A ranking-based feature selection approach for handwritten character recognition,
PRL(121), 2019, pp. 77-86.
Elsevier DOI 1904
Feature selection, Handwritten character recognition BibRef

Cilia, N.D.[Nicole Dalia], d'Alessandro, T.[Tiziana], de Stefano, C.[Claudio], Fontanella, F.[Francesco], Scotto-di Freca, A.[Alessandra],
Comparing filter and wrapper approaches for feature selection in handwritten character recognition,
PRL(168), 2023, pp. 39-46.
Elsevier DOI 2304
BibRef

Cordella, L.P., de Stefano, C.[Claudio], Fontanella, F.[Francesco], Marrocco, C.,
A feature selection algorithm for handwritten character recognition,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Cordella, L.P., de Stefano, C., Fontanella, F., Marcelli, A.,
Looking for Prototypes by Genetic Programming,
IWICPAS06(152-159).
Springer DOI 0608
BibRef
Earlier:
A Novel Genetic Programming Based Approach for Classification Problems,
CIAP05(727-734).
Springer DOI 0509
BibRef

Cordella, L.P., Foggia, P., Sansone, C., Tortorella, F., Vento, M.,
Prototyping Structural Shape Descriptions by Inductive Learning,
VF01(484 ff.).
Springer DOI 0209
BibRef

de Stefano, C.[Claudio], della Cioppa, A., Marcelli, A., Matarazzo, F.,
Grouping Character Shapes by Means of Genetic Programming,
VF01(504 ff.).
Springer DOI 0209
BibRef

de Stefano, C., della Cioppa, A., Marcelli, A.,
Learning handwriting by evolution: a conceptual framework for performance evaluation and tuning,
PR(35), No. 5, May 2002, pp. 1025-1037.
Elsevier DOI 0202
BibRef

de Stefano, C.[Claudio], Garruto, M.[Marco], Lapresa, L.[Luis], Marcelli, A.[Angelo],
Using Strings for On-Line Handwriting Shape Matching: A New Weighted Edit Distance,
CIAP05(1125-1132).
Springer DOI 0509
BibRef

de Stefano, C., Garruto, M., Marcelli, A.,
A multiresolution approach to on-line handwriting segmentation and feature extraction,
ICPR04(II: 614-617).
IEEE DOI 0409
BibRef

Hanmandlu, M., Murali Mohan, K.R., Chakraborty, S.[Sourav], Goyal, S.[Sumeer], Choudhury, D.R.[D. Roy],
Unconstrained handwritten character recognition based on fuzzy logic,
PR(36), No. 3, March 2003, pp. 603-623.
Elsevier DOI 0301
BibRef

Hanmandlu, M., Murali Mohan, K.R., Chakraborty, S.[Sourav], Goyal, S.[Sumeer],
Fuzzy Logic Based Handwritten Character Recognition,
ICIP01(III: 42-45).
IEEE DOI 0108
BibRef

Hanmandlu, M., Murali Mohan, K.R., Gupta, V.,
Fuzzy Logic Based Handwritten Character Recognition 2,
ICIP97(III: 714-717).
IEEE DOI 9710
BibRef

Chakravarthy, V.S.[V. Srinivasa], Kompella, B.[Bhaskar],
The shape of handwritten characters,
PRL(24), No. 12, August 2003, pp. 1901-1913.
Elsevier DOI 0304
BibRef

Gangadhar, G.[Garipelli], Joseph, D.[Denny], Chakravarthy, V.S.[V. Srinivasa],
An oscillatory neuromotor model of handwriting generation,
IJDAR(10), No. 2, November 2007, pp. 69-84.
Springer DOI 0711
BibRef

Aksela, M.[Matti], Girdziusas, R.[Ramunas], Laaksonen, J.T.[Jorma T.], Oja, E.[Erkki], Kangas, J.[Jari],
Methods for adaptive combination of classifiers with application to recognition of handwritten characters,
IJDAR(6), No. 1, 2003, pp. 23-41.
Springer DOI 0308
BibRef
Earlier: A1, A3, A4, A5, Only:
Rejection methods for an adaptive committee classifier,
ICDAR01(982-986).
IEEE DOI 0109
BibRef

Aksela, M.[Matti], Laaksonen, J.T.[Jorma T.],
Adaptive combination of adaptive classifiers for handwritten character recognition,
PRL(28), No. 1, 1 January 2007, pp. 136-143.
Elsevier DOI 0611
Classifier combining; Adaptive classifiers; Adaptive committee; On-line adaptation; Handwritten character recognition BibRef

Chou, C.H.[Chien-Hsing], Lin, C.C.[Chin-Chin], Liu, Y.H.[Ying-Ho], Chang, F.[Fu],
A prototype classification method and its use in a hybrid solution for multiclass pattern recognition,
PR(39), No. 4, April 2006, pp. 624-634.
Elsevier DOI 0604
Fuzzy c-means clustering algorithm; Handwritten character recognition; Hybrid classifier; K-means clustering algorithm; Prototype learning; Support vector machine BibRef

Oncina, J.[Jose], Sebban, M.[Marc],
Learning stochastic edit distance: Application in handwritten character recognition,
PR(39), No. 9, September 2006, pp. 1575-1587.
Elsevier DOI 0606
BibRef
Earlier:
Using Learned Conditional Distributions as Edit Distance,
SSPR06(403-411).
Springer DOI 0608
Stochastic edit distance; Finite-state transducers
See also Learning state machine-based string edit kernels. BibRef

Micó, L.[Luisa], Oncina, J.[Jose],
A log square average case algorithm to make insertions in fast similarity search,
PRL(33), No. 9, 1 July 2012, pp. 1060-1065.
Elsevier DOI 1202
Similarity search; Metric space; Dynamic index; Insertions BibRef

Gagné, C.[Christian], Parizeau, M.[Marc],
Genetic engineering of hierarchical fuzzy regional representations for handwritten character recognition,
IJDAR(8), No. 4, September 2006, pp. 223-231.
Springer DOI 0609
BibRef

Lemieux, A., Gagné, C.[Christian], Parizeau, M.[Marc],
Genetical engineering of handwriting representations,
FHR02(145-150).
IEEE Top Reference. 0209
BibRef

Parizeau, M., Lemieux, A., Gagne, C.,
Character recognition experiments using Unipen data,
ICDAR01(481-485).
IEEE DOI 0109
BibRef

Soares de Oliveira, L.E.[Luiz E.], Morita, M.[Marisa], Sabourin, Jr., R.[Robert],
Feature selection for ensembles applied to handwriting recognition,
IJDAR(8), No. 4, September 2006, pp. 262-279.
Springer DOI 0609

See also Impacts of verification on a numeral string recognition system. BibRef

Soares de Oliveira, L.E.[Luiz E.], Sabourin, Jr., R.[Robert], Bortolozzi, F., Suen, C.Y.,
Feature selection for ensembles: A hierarchical multi-objective genetic algorithm approach,
ICDAR03(676-680).
IEEE DOI 0311
BibRef

Hirabara, L.Y.[Luciane Y.], Aires, S.B.K.[Simone B.K.], de A. Freitas, C.O.[Cinthia O.], de Souza Britto, Jr., A.[Alceu], Sabourin, R.[Robert],
Dynamic Zoning Selection for Handwritten Character Recognition,
CIARP11(507-514).
Springer DOI 1111
BibRef

Plötz, T.[Thomas], Fink, G.A.[Gernot A.],
Markov models for offline handwriting recognition: a survey,
IJDAR(12), No. 4, December 2009, pp. xx-yy.
Springer DOI 0912
Survey, Handwriting. BibRef

Pauplin, O.[Olivier], Jiang, J.M.[Jian-Min],
DBN-based structural learning and optimisation for automated handwritten character recognition,
PRL(33), No. 6, 15 April 2012, pp. 685-692.
Elsevier DOI 1203
Pattern classification; Dynamic Bayesian Network; Structure learning; Supervised learning; Handwritten character recognition; Evolutionary Algorithm BibRef

Liwicki, M.[Marcus], Ebert, S.[Sebastian], Dengel, A.[Andreas],
Bridging the gap between handwriting recognition and knowledge management,
PRL(35), No. 1, 2014, pp. 204-213.
Elsevier DOI 1312
Handwriting recognition BibRef

Vajda, S.[Szilárd], Rangoni, Y.[Yves], Cecotti, H.[Hubert],
Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition,
PRL(58), No. 1, 2015, pp. 23-28.
Elsevier DOI 1505
Character recognition BibRef

Costagliola, G., de Rosa, M., Fuccella, V.,
Handwriting on Smartwatches: An Empirical Investigation,
HMS(47), No. 6, December 2017, pp. 1100-1109.
IEEE DOI 1712
Character recognition, Handwriting recognition, Keyboards, Performance evaluation, Text recognition, Wearable computing, wristwatch BibRef

Zhang, Y.P.[Ya-Ping], Liang, S.[Shan], Nie, S.[Shuai], Liu, W.J.[Wen-Ju], Peng, S.[Shouye],
Robust offline handwritten character recognition through exploring writer-independent features under the guidance of printed data,
PRL(106), 2018, pp. 20-26.
Elsevier DOI 1804
Handwritten character recognition, Writer-independent features, Adversarial feature learning, Convolutional neural network BibRef

Ptucha, R.[Raymond], Such, F.P.[Felipe Petroski], Pillai, S.[Suhas], Brockler, F.[Frank], Singh, V.[Vatsala], Hutkowski, P.[Paul],
Intelligent character recognition using fully convolutional neural networks,
PR(88), 2019, pp. 604-613.
Elsevier DOI 1901
Handwriting recognition, Fully convolutional neural networks, Deep learning BibRef

Liu, Y.L.[Yu-Liang], Jin, L.W.[Lian-Wen], Lai, S.X.[Song-Xuan],
Automatic labeling of large amounts of handwritten characters with gate-guided dynamic deep learning,
PRL(119), 2019, pp. 94-102.
Elsevier DOI 1902
Automatic labeling, Handwritten characters, Path signature, Gate guided BibRef

Moysset, B.[Bastien], Messina, R.[Ronaldo],
Are 2D-LSTM really dead for offline text recognition?,
IJDAR(22), No. 3, September 2019, pp. 193-208.
Springer DOI 1909
BibRef

Yousef, M.[Mohamed], Hussain, K.F.[Khaled F.], Mohammed, U.S.[Usama S.],
Accurate, data-efficient, unconstrained text recognition with convolutional neural networks,
PR(108), 2020, pp. 107482.
Elsevier DOI 2008
Text recognition, Optical character recognition, Handwriting recognition, CAPTCHA Solving, Deep learning BibRef

Kotani, A.[Atsunobu], Tellex, S.[Stefanie], Tompkin, J.[James],
Generating Handwriting via Decoupled Style Descriptors,
ECCV20(XII: 764-780).
Springer DOI 2010
BibRef

Liu, X.Y.[Xi-Yan], Meng, G.F.[Gao-Feng], Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
Handwritten Text Generation via Disentangled Representations,
SPLetters(28), 2021, pp. 1838-1842.
IEEE DOI 2109
Training, Gaussian distribution, Text recognition, Image reconstruction, Task analysis, Generators, Convolution, deep learning BibRef

Kojic, T.[Tanja], Vergari, M.[Maurizio], Möller, S.[Sebastian], Voigt-Antons, J.N.[Jan-Niklas],
Assessing User Experience of Text Readability with Eye Tracking in Virtual Reality,
VAMR22(I:199-211).
Springer DOI 2206
BibRef

Ao, X.[Xiang], Zhang, X.Y.[Xu-Yao], Liu, C.L.[Cheng-Lin],
Cross-modal prototype learning for zero-shot handwritten character recognition,
PR(131), 2022, pp. 108859.
Elsevier DOI 2208
Online handwriting, Offline handwriting, Printed character, Zero-shot, Prototype, Cross-modality BibRef

Dhiaf, M.[Marwa], Rouhou, A.C.[Ahmed Cheikh], Kessentini, Y.[Yousri], Ben Salem, S.[Sinda],
MSdocTr-Lite: A lite transformer for full page multi-script handwriting recognition,
PRL(169), 2023, pp. 28-34.
Elsevier DOI 2305
Seq2Seq model, Page-level recognition, Handwritten text recognition, Multi-script, Transformer, Transfer learning BibRef

Coquenet, D.[Denis], Chatelain, C.[Clément], Paquet, T.[Thierry],
DAN: A Segmentation-Free Document Attention Network for Handwritten Document Recognition,
PAMI(45), No. 7, July 2023, pp. 8227-8243.
IEEE DOI 2306
Layout, Text recognition, Task analysis, Image segmentation, Handwriting recognition, Transformers, Annotations, transformer BibRef

Vidal, E.[Enrique], Toselli, A.H.[Alejandro H.], Ríos-Vila, A.[Antonio], Calvo-Zaragoza, J.[Jorge],
End-to-End page-Level assessment of handwritten text recognition,
PR(142), 2023, pp. 109695.
Elsevier DOI 2307
Handwritten text recognition, Full-Page end-to-End text image transcription, Word error rate BibRef

Zhou, Y.[Yunyu], Minematsu, T.[Tsubasa], Shimada, A.[Atsushi],
Improvement of Image Segmentation Model for Handwritten Notebook Analytics,
ICIP23(1870-1874)
IEEE DOI 2312
BibRef

Pippi, V.[Vittorio], Cascianelli, S.[Silvia], Cucchiara, R.[Rita],
Handwritten Text Generation from Visual Archetypes,
CVPR23(22458-22467)
IEEE DOI 2309
BibRef

Zhang, X.Y.[Xiao-Yi], Wang, J.P.[Jia-Peng], Jin, L.W.[Lian-Wen], Ren, Y.J.[Yu-Jin], Xue, Y.[Yang],
CMT-CO: Contrastive Learning with Character Movement Task for Handwritten Text Recognition,
ACCV22(VII:626-642).
Springer DOI 2307
BibRef

Heil, R.[Raphaela], Breznik, E.[Eva],
A Study of Augmentation Methods for Handwritten Stenography Recognition,
IbPRIA23(134-145).
Springer DOI 2307
BibRef

Cascianelli, S.[Silvia], Cornia, M.[Marcella], Baraldi, L.[Lorenzo], Piazzi, M.L.[Maria Ludovica], Schiuma, R.[Rosiana], Cucchiara, R.[Rita],
Learning to Read L'Infinito: Handwritten Text Recognition with Synthetic Training Data,
CAIP21(II:340-350).
Springer DOI 2112
BibRef

Bhunia, A.K.[Ayan Kumar], Ghose, S.[Shuvozit], Kumar, A.[Amandeep], Chowdhury, P.N.[Pinaki Nath], Sain, A.[Aneeshan], Song, Y.Z.[Yi-Zhe],
MetaHTR: Towards Writer-Adaptive Handwritten Text Recognition,
CVPR21(15825-15834)
IEEE DOI 2111
Adaptation models, Adaptive systems, Text recognition, Computational modeling, Computer architecture, Writing BibRef

Cojocaru, I.[Iulian], Cascianelli, S.[Silvia], Baraldi, L.[Lorenzo], Corsini, M.[Massimiliano], Cucchiara, R.[Rita],
Watch Your Strokes: Improving Handwritten Text Recognition with Deformable Convolutions,
ICPR21(6096-6103)
IEEE DOI 2105
Handwriting recognition, Adaptation models, Convolution, Text recognition, Benchmark testing, Writing, Distance measurement BibRef

Jayasundara, V., Jayasekara, S., Jayasekara, H., Rajasegaran, J., Seneviratne, S., Rodrigo, R.,
TextCaps: Handwritten Character Recognition With Very Small Datasets,
WACV19(254-262)
IEEE DOI 1904
handwritten character recognition, learning (artificial intelligence), object recognition, Task analysis BibRef

Clark-Younger, H., Mills, S., Szymanski, L.,
Stacked Hourglass CNN for Handwritten Character Location,
IVCNZ18(1-6)
IEEE DOI 1902
Training, Heating systems, Task analysis, Character recognition, Keyword search, Semantics, character recognition BibRef

Tang, W., Yu, P., Zhou, J., Wu, Y.,
Towards a Unified Compositional Model for Visual Pattern Modeling,
ICCV17(2803-2812)
IEEE DOI 1802
backpropagation, character recognition, graph theory, handwritten character recognition, image recognition, Visualization BibRef

Peymani, K., Soryani, M.,
From machine generated to handwritten character recognition; a deep learning approach,
IPRIA17(243-247)
IEEE DOI 1712
feedforward neural nets, handwritten character recognition, Optical Character Recognition BibRef

Ayyalasomayajula, K.R.[Kalyan Ram], Nettelblad, C.[Carl], Brun, A.[Anders],
Feature Evaluation for Handwritten Character Recognition with Regressive and Generative Hidden Markov Models,
ISVC16(I: 278-287).
Springer DOI 1701
BibRef

Amara, M.[Marwa], Zidi, K.[Kamel], Ghedira, K.[Khaled],
Towards a Generic M-SVM Parameters Estimation Using Overlapping Swarm Intelligence for Handwritten Characters Recognition,
ACIVS16(498-509).
Springer DOI 1611
BibRef

El-Sana, J.[Jihad], Kedem, K.[Klara],
Word of blobs,
ICDAR15(1016-1020)
IEEE DOI 1511
Blobs that resemble the strokes. BibRef

Hyuga, T., Wada, H., Aizawa, T., Ijiri, Y., Kawade, M.,
Deformed and Touched Characters Recognition,
ACPR13(744-745)
IEEE DOI 1408
computer vision BibRef

Cecotti, H.[Hubert], Vajda, S.[Szilárd],
A Radial Neural Convolutional Layer for Multi-oriented Character Recognition,
ICDAR13(668-672)
IEEE DOI 1312
BibRef
And:
Rejection Schemes in Multi-class Classification: Application to Handwritten Character Recognition,
ICDAR13(445-449)
IEEE DOI 1312
handwritten character recognition Radon transforms. BibRef

Roy, U., Sankaran, N., Sankar, K.P., Jawahar, C.V.,
Character N-Gram Spotting on Handwritten Documents Using Weakly-Supervised Segmentation,
ICDAR13(577-581)
IEEE DOI 1312
handwritten character recognition BibRef

Breuel, T.M., Ul-Hasan, A., Al-Azawi, M.A., Shafait, F.,
High-Performance OCR for Printed English and Fraktur Using LSTM Networks,
ICDAR13(683-687)
IEEE DOI 1312
handwriting recognition BibRef

Ciresan, D.C.[Dan Claudiu], Meier, U.[Ueli], Gambardella, L.M.[Luca Maria], Schmidhuber, J.[Jurgen],
Convolutional Neural Network Committees for Handwritten Character Classification,
ICDAR11(1135-1139).
IEEE DOI 1111
BibRef

Gao, Y.[Yan], Jin, L.[Lanwen], He, C.[Cong], Zhou, G.[Guibin],
Handwriting Character Recognition as a Service: A New Handwriting Recognition System Based on Cloud Computing,
ICDAR11(885-889).
IEEE DOI 1111
BibRef

Miyoshi, T.[Toshinori], Shinjo, H.[Hiroshi], Nagasaki, T.[Takeshi],
Simplified polynomial network classifier for handwritten character recognition,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Schlapbach, A.[Andreas], Wettstein, F.[Frank], Bunke, H.[Horst],
Estimating the readability of handwritten text: A Support Vector Regression based approach,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Thome, N., Vacavant, A.,
A Combined Statistical-Structural Strategy for Alphanumeric Recognition,
ISVC07(II: 529-538).
Springer DOI 0711
BibRef

Sadri, J.[Javad], Suen, C.Y.[Ching Y.], Bui, T.D.[Tien D.],
A New Clustering Method for Improving Plasticity and Stability in Handwritten Character Recognition Systems,
ICPR06(II: 1130-1133).
IEEE DOI 0609
BibRef

Miyao, H.[Hidetoshi], Maruyama, M.[Minoru],
Virtual Example Synthesis Based on PCA for Off-Line Handwritten Character Recognition,
DAS06(96-105).
Springer DOI 0602

See also online handwritten music symbol recognition system, An.
See also On-Line Handwritten flowchart Recognition, Beautification and Editing System. BibRef

Miyao, H., Maruyama, M., Nakano, Y., Hananoi, T.,
Off-line handwritten character recognition by SVM based on the virtual examples synthesized from on-line characters,
ICDAR05(I: 494-498).
IEEE DOI 0508
BibRef

Liu, Y.[Yang], Liu, X.B.[Xia-Bi], Jia, Y.D.[Yun-De],
Hand-Gesture Based Text Input for Wearable Computers,
CVS06(8).
IEEE DOI 0602
Write the character by the fingertip. BibRef

Keysers, D., Gollan, C., Ney, H.,
Local context in non-linear deformation models for handwritten character recognition,
ICPR04(IV: 511-514).
IEEE DOI 0409
BibRef

Sun, G.[Guangling], Huang, J.H.[Jian-Hua], Tang, X.L.[Xiang-Long],
Active discriminant functions for handwriting recognition,
ICPR04(II: 602-605).
IEEE DOI 0409
BibRef

Chang, F.[Fu], Lin, C.C.[Chin-Chin], Chen, C.J.[Chun-Jen],
Applying a hybrid method to handwritten character recognition,
ICPR04(II: 529-532).
IEEE DOI 0409
BibRef

Noor, N.M., Razaz, M., Manley-Cooke, P.,
Global geometry extraction for fuzzy logic based handwritten character recognition,
ICPR04(II: 513-516).
IEEE DOI 0409
BibRef

Ellozy, H.A.[Hamed A.], Jeanty, H.H.[Henry H.], Tappert, C.C.[Charles C.],
Handwriting recognition employing pairwise discriminant measures,
US_Patent5,005,205, April 2, 1991.
WWW Link. BibRef 9104

Cha, S.H.[Sung-Hyuk], Yoon, S.S.[Sung-Soo], Tappert, C.C.,
On binary similarity measures for handwritten character recognition,
ICDAR05(I: 4-8).
IEEE DOI 0508
BibRef

Cha, S.H.[Sung-Hyuk], Tappert, C.C., Srihari, S.N.,
Optimizing binary feature vector similarity measure using genetic algorithm and handwritten character recognition,
ICDAR03(662-665).
IEEE DOI 0311
BibRef

Feldbach, M., Tönnies, K.D.,
Word segmentation of handwritten dates in historical documents by combining semantic a-priori-knowledge with local features,
ICDAR03(333-337).
IEEE DOI 0311
BibRef
Earlier:
Segmentation of the Date in Entries of Historical Church Registers,
DAGM02(403 ff.).
Springer DOI 0303
BibRef
Earlier:
Line detection and segmentation in historical church registers,
ICDAR01(743-747).
IEEE DOI 0109
BibRef

Cho, S.J.[Sung-Jung], Perrone, M.P., Ratzlaff, E.,
Probability table compression for handwritten character recognition,
ICDAR03(173-177).
IEEE DOI 0311
BibRef

Nopsuwanchai, R., Povey, D.,
Discriminative training for HMM-based of fine handwritten character recognition,
ICDAR03(114-118).
IEEE DOI 0311
BibRef

Wada, Y., Kasuga, H., Sumita, K.,
An evolutionary approach for the generation of diversiform characters using a handwriting model,
ICPR02(III: 131-134).
IEEE DOI 0211
BibRef

Mori, M.,
Video text recognition using feature compensation as category-dependent feature extraction,
ICDAR03(645-649).
IEEE DOI 0311
BibRef

Mori, M., Sawaki, M., Hagita, N.,
Category-dependent feature extraction for recognition of degraded handwritten characters,
ICPR02(III: 155-159).
IEEE DOI 0211
BibRef

Mori, M., Sawaki, M., Hagita, N., Murase, H., Mukawa, N.,
Robust feature extraction based on run-length compensation for degraded handwritten character recognition,
ICDAR01(650-654).
IEEE DOI 0109
BibRef

Lam, L., Xu, Q.Z.[Qi-Zhi], Suen, C.Y.,
Differentiation between alphabetic and numeric data using NN ensembles,
ICPR02(IV: 40-43).
IEEE DOI 0211
BibRef

Zhu, X.Y.[Xiao-Yan], Shi, Y.F.[Yi-Fan],
A handwritten character recognition method with ANN feedback,
ICDAR01(255-259).
IEEE DOI 0109
BibRef
And:
A New Algorithm for Handwritten Character Recognition,
ICIP01(I: 1130-1133).
IEEE DOI 0108
BibRef

Arlandis, J.[Joaquim], Perez-Cortes, J.C.[Juan-Carlos], Llobet, R.[Rafael],
Handwritten Character Recognition Using the Continuos Distance Transformation,
ICPR00(Vol I: 940-943).
IEEE DOI 0009
BibRef

Miller, E.G.[Erik G.], Matsakis, N.E.[Nicholas E.], Viola, P.A.[Paul A.],
Learning from One Example through Shared Densities on Transforms,
CVPR00(I: 464-471).
IEEE DOI 0005
Learning BibRef

Prema, K.V., Reddy, N.V.S.,
Neural Network Based Handwritten Character Recognition for Conflict Resolution,
MVA98(xx-yy). BibRef 9800

Waizumi, Y., Kato, N., Saruta, K., Nemoto, Y.,
High Speed Rough Classification for Handwritten Characters Using Hierarchical Learning Vector Quantization,
ICDAR97(23-27).
IEEE DOI 9708
BibRef

Matsumura, S., Kobayashi, T., Nakamura, O., Ogura, K.,
Document Input According to Recognition Accuracy of Handwritten Characters,
ICDAR97(51-55).
IEEE DOI 9708
BibRef

Rodrigues Gomes, N., Lee, L.L.[Luan Ling],
Feature extraction based on fuzzy set theory for handwriting recognition,
ICDAR01(655-659).
IEEE DOI 0109
BibRef

Lee, L.L.[Luan Ling], Rodrigues Gomes, N.,
Disconnected Handwritten Character Image Recognition,
ICDAR97(467-470).
IEEE DOI 9708
BibRef

Gloger, J.M., Kaltenmeier, A., Mandler, E., Andrews, L.,
Reject Management in a Handwriting Recognition System,
ICDAR97(556-559).
IEEE DOI 9708
BibRef

Kimura, F., Kayahara, N., Miyake, Y., Shridhar, M.,
Machine and human recognition of segmented characters from handwritten words,
ICDAR97(866-869).
IEEE DOI 9708
BibRef

Park, H.S.[Hee-Seon], Lee, S.W.[Seong-Whan],
An HMMRF-based statistical approach for off-line handwritten character recognition,
ICPR96(II: 320-324).
IEEE DOI 9608
(Korea Univ., KOR) BibRef

Gong, Y., Boyer, A.,
Hand-written text recognition based on a new formulation,
ICPR92(II:112-115).
IEEE DOI 9208
BibRef

Yokozuka, S., Kida, H.,
An application of feature selection to handwritten character recognition,
ICPR92(II:537-540).
IEEE DOI 9208
BibRef

Kimura, M., Ejima, T., Aso, H., Yashiro, H., Son, N., Suzuki, M.,
An Intelligent Character Recognition System with High Accuracy and High Speed by Integrating Image-Type and Logical-Type Information Processings,
ICPR88(I: 38-40).
IEEE DOI BibRef 8800

Holder, S., Dengler, J.,
Font- and Size-Invariant Character Recognition with Greyvalue Image Features,
ICPR88(I: 252-254).
IEEE DOI 8811
BibRef

Leveridge, P.C., Leedham, C.G.,
Experiments with an N-Tuple Recogniser for Fast 'First Try' Recognition of Unconstrained Handwritten Symbols,
ICPR88(II: 905-907).
IEEE DOI 8811
BibRef

Lettera, C., Masera, L., Paoli, C., Porinelli, R.,
Use of a Dictionary in Conjunction with a Handwritten Texts Recognizer,
ICPR86(699-701). BibRef 8600

Sagawa, T., Tanaka, E., Suzuki, M., Fujita, M.,
An Unsupervised Learning of Hand-Printed Characters with Linguistic Information,
ICPR84(766-769). BibRef 8400

Kuklinski, T.T.,
Components of Handprint Style Variabilty,
ICPR84(924-926). BibRef 8400

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Handwritten Characters, Feature Extraction .