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FHR12(143-148).
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1302
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ICDAR11(1095-1099).
IEEE DOI
1111
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ICPR10(2873-2876).
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Affine-invariant template matching
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Enhanced GPT Correlation for 2D Projection Transformation Invariant
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Springer DOI
1511
BibRef
Earlier: A2, A2:
GPT Correlation for 2D Projection Transformation Invariant Template
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ICPR14(3810-3815)
IEEE DOI
1412
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And: A1, A2:
k-NN Classification of Handwritten Characters Using a New
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ICPR14(262-267)
IEEE DOI
1412
Matching.
Computational modeling.
Acceleration
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Moments.
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Efficient detection of abnormalities in large OCR databases,
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9708
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9712
Generate description using large family of binary features (every
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Apply to NIST dataset.
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See also Face recognition using the mixture-of-eigenfaces method.
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0208
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Earlier:
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IEEE DOI
0005
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Chen, G.Y.,
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0304
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Chen, G.Y.,
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IEEE DOI
0508
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Earlier: A1, A3, A2:
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IEEE DOI
0408
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Bellili, A.,
Gilloux, M.,
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An MLP-SVM combination architecture for offline handwritten digit
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Springer DOI
0308
BibRef
Earlier:
An hybrid MLP-SVM handwritten digit recognizer,
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IEEE DOI
0109
BibRef
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Combination of the assembly neural network with a perceptron for
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0412
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Parkins, A.D.,
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VISP(152), No. 2, April 2005, pp. 137-147.
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0510
BibRef
Sung, J.M.[Jae-Mo],
Bang, S.Y.[Sung-Yang],
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A Bayesian network classifier and hierarchical Gabor features for
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PRL(27), No. 1, 1 January 2006, pp. 66-75.
Elsevier DOI
0512
BibRef
Sung, J.M.[Jae-Mo],
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PAMI(30), No. 12, December 2008, pp. 2236-2242.
IEEE DOI
0811
BibRef
Sung, J.M.[Jae-Mo],
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Springer DOI
0306
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Savas, B.[Berkant],
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PR(40), No. 3, March 2007, pp. 993-1003.
Elsevier DOI
0611
Tensors; Higher order singular value decomposition;
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Hoffmann, H.[Heiko],
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PR(40), No. 3, March 2007, pp. 863-874.
Elsevier DOI
0611
Kernel method; Novelty detection; PCA; Handwritten digit; Breast cancer
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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
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Lauer, F.[Fabien],
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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
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Hanmandlu, M.[Madasu],
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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
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Hanmandlu, M.[Madasu],
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Madasu, V.K.[Vamsi Krishna],
Fuzzy Modeling Based Recognition of Multi-font Numerals,
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Springer DOI
0310
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Zhang, P.[Ping],
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A novel cascade ensemble classifier system with a high recognition
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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
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Zhou, J.[Jie],
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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);
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Handwritten numeral recognition; Gene expression classification
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Kherallah, M.[Monji],
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Elsevier DOI
0802
Handwriting modeling; Stroke overlapping; Elliptic trajectory modeling;
Beta velocity modeling; Digit recognition
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Vellasques, E.,
Oliveira, L.S.,
de Souza Britto, Jr., A.[Alceu],
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Elsevier DOI
0808
Segmentation; Filtering
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Ko, A.H.R.[Albert Hung-Ren],
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IEEE DOI
0911
Generally HMM have a problem with noise. Improves recognition from 98%
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See also Evaluation of incremental learning algorithms for HMM in the recognition of alphanumeric characters.
BibRef
Oliveira, L.S.,
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Sabourin, R.,
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IEEE DOI
0508
BibRef
Ng, G.S.[Geok See],
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Shi, D.M.[Da-Ming],
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0610
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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],
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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],
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Invariance analysis of modified C2 features: case study:
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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
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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
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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
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ICIAR13(124-132).
Springer DOI
1307
BibRef
Sermanet, P.[Pierre],
Chintala, S.[Soumith],
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Convolutional neural networks applied to house numbers digit
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ICPR12(3288-3291).
WWW Link.
1302
BibRef
Yu, X.G.[Xin-Guo],
Localization and extraction of the four clock-digits using the
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ICPR12(1217-1220).
WWW Link.
1302
Not handwritten
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Barbuzzi, D.[Donato],
Impedovo, D.[Donato],
Learning Iterative Strategies in Multi-Expert Systems Using SVMs for
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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,
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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],
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A biologically inspired system for fast handwritten digit recognition,
ICIP11(1749-1752).
IEEE DOI
1201
BibRef
de Santana Pereira, C.[Cristiano],
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Handwritten connected digits detection:
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ICIP11(2613-2616).
IEEE DOI
1201
BibRef
Li, P.[Peng],
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The research on arabic numeral symbol's use in poster design,
IASP11(67-70).
IEEE DOI
1112
Not recognition, but history.
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Gimenez, A.[Adria],
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Discriminative Bernoulli Mixture Models for Handwritten Digit
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ICDAR11(558-562).
IEEE DOI
1111
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Mizukami, Y.[Yoshiki],
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CUDA Implementation of Deformable Pattern Recognition and its
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IEEE DOI
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Lawal, I.A.[Isah A.],
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Recognition of Handwritten Numerical Fields in a Large Single-Writer
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0907
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A Wavelet-Based Descriptor for Handwritten Numeral Classification,
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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],
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Alamri, H.[Huda],
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A New Approach for Segmentation and Recognition of Arabic Handwritten
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CAIP09(165-172).
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0909
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Yu, X.G.[Xin-Guo],
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IEEE DOI
0812
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0809
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Yektaii, M.[Mahdi],
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Cumulative Global Distance for Dimension Reduction in Handwritten
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0706
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Unsupervised Selection and Discriminative Estimation of Orthogonal
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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
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ICDAR07(347-351).
IEEE DOI
0709
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Zheng, L.H.[Li-Hong],
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IEEE DOI
0612
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Style Quantification of Scanned Multi-source Digits,
ICPR06(II: 1018-10121).
IEEE DOI
0609
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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
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0508
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Fan, X.D.[Xiao-Dong],
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Rather than multiple classifiers, 1 per object class, a hierarchical approach.
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Ng, G.S.,
Murali, T.,
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Miller, E.G.[Erik G.],
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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.,
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Maruyama, M.,
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ICDAR03(359-363).
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0311
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Valveny, E.,
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Numeral recognition for quality control of surgical sachets,
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IEEE DOI
0311
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Muramatsu, H.,
Kobayashi, T.,
Sugiyama, T.,
Abe, K.,
Improvement of matching and evaluation in handwritten numeral
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ICDAR03(273-277).
IEEE DOI
0311
BibRef
Kobayashi, T.,
Nakamura, K.,
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Sugiyama, T.,
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ICDAR01(612-616).
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0109
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Takahashi, K.,
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A class-modular GLVQ ensemble with outlier learning for handwritten
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ICDAR03(268-272).
IEEE DOI
0311
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Srihari, S.N.,
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Individuality of numerals,
ICDAR03(1096-1100).
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de Avila, S.[Sandra],
Matos, L.[Leonardo],
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Evaluating a Zoning Mechanism and Class-Modular Architecture for
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CIARP07(515-524).
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0711
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Correia, S.E.N.,
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On the performance of wavelets for handwritten numerals recognition,
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IEEE DOI
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Kim, K.K.[Kye Kyung],
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Post-processing scheme for improving recognition performance of
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IEEE DOI
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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
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ICPR02(IV: 31-34).
IEEE DOI
0211
BibRef
Soares de Oliveira, L.E.,
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Bortolozzi, F.,
Sabourin, R.,
A New Segmentation Approach for Handwritten Digits,
ICPR00(Vol II: 323-326).
IEEE DOI
0009
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Ayat, N.E.,
Cheriet, M.,
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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
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ICIP01(I: 1126-1129).
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0108
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Zhang, R.[Rui],
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Zhang, J.Y.[Jia-Yong],
Offline handwritten character recognition based on discriminative
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ICDAR01(221-225).
IEEE DOI
0109
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Ratzlaff, E.H.,
A scanning n-tuple classifier for online recognition of handwritten
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ICDAR01(18-22).
IEEE DOI
0109
BibRef
Ye, X.Y.[Xiang-Yun],
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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
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ICDAR01(1215-1219).
IEEE DOI
0109
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Singh, S.,
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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 .