| Year |
Citation |
Score |
| 2021 |
Zyblewski P, Sabourin R, Woźniak M. Preprocessed dynamic classifier ensemble selection for highly imbalanced drifted data streams Information Fusion. 66: 138-154. DOI: 10.1016/J.Inffus.2020.09.004 |
0.423 |
|
| 2020 |
Hafemann LG, Sabourin R, Oliveira LS. Meta-Learning for Fast Classifier Adaptation to New Users of Signature Verification Systems Ieee Transactions On Information Forensics and Security. 15: 1735-1745. DOI: 10.1109/Tifs.2019.2949425 |
0.386 |
|
| 2020 |
Souza VL, Oliveira AL, Cruz RM, Sabourin R. A white-box analysis on the writer-independent dichotomy transformation applied to offline handwritten signature verification Expert Systems With Applications. 154: 113397. DOI: 10.1016/J.Eswa.2020.113397 |
0.44 |
|
| 2019 |
Cruz RMO, Souza MA, Sabourin R, Cavalcanti GDC. Dynamic Ensemble Selection and Data Preprocessing for Multi-Class Imbalance Learning International Journal of Pattern Recognition and Artificial Intelligence. 33: 1940009. DOI: 10.1142/S0218001419400093 |
0.415 |
|
| 2019 |
Hafemann LG, Sabourin R, Oliveira LS. Characterizing and Evaluating Adversarial Examples for Offline Handwritten Signature Verification Ieee Transactions On Information Forensics and Security. 14: 2153-2166. DOI: 10.1109/Tifs.2019.2894031 |
0.429 |
|
| 2019 |
Cao H, Bernard S, Sabourin R, Heutte L. Random forest dissimilarity based multi-view learning for Radiomics application Pattern Recognition. 88: 185-197. DOI: 10.1016/J.Patcog.2018.11.011 |
0.444 |
|
| 2019 |
Souza MA, Cavalcanti GD, Cruz RM, Sabourin R. Online local pool generation for dynamic classifier selection Pattern Recognition. 85: 132-148. DOI: 10.1016/J.Patcog.2018.08.004 |
0.413 |
|
| 2019 |
Cruz RM, Oliveira DV, Cavalcanti GD, Sabourin R. FIRE-DES++: Enhanced online pruning of base classifiers for dynamic ensemble selection Pattern Recognition. 85: 149-160. DOI: 10.1016/J.Patcog.2018.07.037 |
0.353 |
|
| 2018 |
Hochuli A, Oliveira L, Britto Jr A, Sabourin R. Handwritten digit segmentation: Is it still necessary? Pattern Recognition. 78: 1-11. DOI: 10.1016/J.Patcog.2018.01.004 |
0.417 |
|
| 2018 |
Brun AL, Britto AS, Oliveira LS, Enembreck F, Sabourin R. A framework for dynamic classifier selection oriented by the classification problem difficulty Pattern Recognition. 76: 175-190. DOI: 10.1016/J.Patcog.2017.10.038 |
0.441 |
|
| 2018 |
Roy A, Cruz RM, Sabourin R, Cavalcanti GD. A study on combining dynamic selection and data preprocessing for imbalance learning Neurocomputing. 286: 179-192. DOI: 10.1016/J.Neucom.2018.01.060 |
0.416 |
|
| 2018 |
Cruz RM, Sabourin R, Cavalcanti GD. Dynamic classifier selection: Recent advances and perspectives Information Fusion. 41: 195-216. DOI: 10.1016/J.Inffus.2017.09.010 |
0.414 |
|
| 2018 |
Almeida PR, Oliveira LS, Britto AS, Sabourin R. Adapting dynamic classifier selection for concept drift Expert Systems With Applications. 104: 67-85. DOI: 10.1016/J.Eswa.2018.03.021 |
0.405 |
|
| 2018 |
Hafemann LG, Oliveira LS, Sabourin R. Fixed-sized representation learning from offline handwritten signatures of different sizes International Journal On Document Analysis and Recognition (Ijdar). 21: 219-232. DOI: 10.1007/S10032-018-0301-6 |
0.406 |
|
| 2017 |
Oliveira DV, Cavalcanti GD, Sabourin R. Online pruning of base classifiers for Dynamic Ensemble Selection Pattern Recognition. 72: 44-58. DOI: 10.1016/J.Patcog.2017.06.030 |
0.406 |
|
| 2017 |
Hafemann LG, Sabourin R, Oliveira LS. Learning features for offline handwritten signature verification using deep convolutional neural networks Pattern Recognition. 70: 163-176. DOI: 10.1016/J.Patcog.2017.05.012 |
0.448 |
|
| 2017 |
Bashbaghi S, Granger E, Sabourin R, Bilodeau G. Dynamic ensembles of exemplar-SVMs for still-to-video face recognition Pattern Recognition. 69: 61-81. DOI: 10.1016/J.Patcog.2017.04.014 |
0.432 |
|
| 2017 |
Cruz RM, Sabourin R, Cavalcanti GD. META-DES.Oracle: Meta-learning and feature selection for dynamic ensemble selection Information Fusion. 38: 84-103. DOI: 10.1016/J.Inffus.2017.02.010 |
0.484 |
|
| 2016 |
Diaz M, Ferrer MA, Eskander GS, Sabourin R. Generation of Duplicated Off-line Signature Images for Verification Systems. Ieee Transactions On Pattern Analysis and Machine Intelligence. PMID 28113540 DOI: 10.1109/Tpami.2016.2560810 |
0.379 |
|
| 2016 |
Dewan MAA, Granger E, Marcialis G, Sabourin R, Roli F. Adaptive appearance model tracking for still-to-video face recognition Pattern Recognition. 49: 129-151. DOI: 10.1016/J.Patcog.2015.08.002 |
0.382 |
|
| 2016 |
Roy A, Cruz RM, Sabourin R, Cavalcanti GD. Meta-learning recommendation of default size of classifier pool for META-DES Neurocomputing. 216: 351-362. DOI: 10.1016/J.Neucom.2016.08.013 |
0.411 |
|
| 2016 |
Corriveau G, Guilbault R, Tahan A, Sabourin R. Bayesian network as an adaptive parameter setting approach for genetic algorithms Complex & Intelligent Systems. 2: 1-22. DOI: 10.1007/S40747-016-0010-Z |
0.354 |
|
| 2016 |
Cruz RMO, Sabourin R, Cavalcanti GDC. Prototype selection for dynamic classifier and ensemble selection Neural Computing and Applications. 1-11. DOI: 10.1007/S00521-016-2458-6 |
0.42 |
|
| 2015 |
Cruz RMO, Sabourin R, Cavalcanti GDC. META-DES.H: A Dynamic Ensemble Selection technique using meta-learning and a dynamic weighting approach Proceedings of the International Joint Conference On Neural Networks. 2015. DOI: 10.1109/IJCNN.2015.7280594 |
0.338 |
|
| 2015 |
Hafemann LG, Oliveira LS, Cavalin PR, Sabourin R. Transfer learning between texture classification tasks using Convolutional Neural Networks Proceedings of the International Joint Conference On Neural Networks. 2015. DOI: 10.1109/IJCNN.2015.7280558 |
0.772 |
|
| 2015 |
De-La-Torre M, Granger E, Sabourin R. Adaptive skew-sensitive fusion of ensembles and their application to face re-identification Proceedings of the International Joint Conference On Neural Networks. 2015. DOI: 10.1109/IJCNN.2015.7280433 |
0.324 |
|
| 2015 |
Vriesmann LM, Britto AS, Oliveira LS, Koerich AL, Sabourin R. Combining overall and local class accuracies in an oracle-based method for dynamic ensemble selection Proceedings of the International Joint Conference On Neural Networks. 2015. DOI: 10.1109/IJCNN.2015.7280340 |
0.682 |
|
| 2015 |
De-la-Torre M, Gorodnichy DO, Granger E, Sabourin R. Individual-specific management of reference data in adaptive ensembles for face re-identification Iet Computer Vision. 9: 732-740. DOI: 10.1049/Iet-Cvi.2014.0375 |
0.368 |
|
| 2015 |
Bernard S, Chatelain C, Adam S, Sabourin R. The Multiclass ROC Front method for cost-sensitive classification Pattern Recognition. DOI: 10.1016/J.Patcog.2015.10.010 |
0.407 |
|
| 2015 |
De-la-Torre M, Granger E, Sabourin R, Gorodnichy DO. Adaptive skew-sensitive ensembles for face recognition in video surveillance Pattern Recognition. 48: 3385-3406. DOI: 10.1016/J.Patcog.2015.05.008 |
0.437 |
|
| 2015 |
Cruz RMO, Sabourin R, Cavalcanti GDC, Ing Ren T. META-DES: A dynamic ensemble selection framework using meta-learning Pattern Recognition. 48: 1925-1935. DOI: 10.1016/J.Patcog.2014.12.003 |
0.477 |
|
| 2015 |
De-la-Torre M, Granger E, Radtke PV, Sabourin R, Gorodnichy DO. Partially-supervised learning from facial trajectories for face recognition in video surveillance Information Fusion. 24: 31-53. DOI: 10.1016/J.Inffus.2014.05.006 |
0.407 |
|
| 2015 |
Ko AHR, Jousselme AL, Sabourin R, Gagnon F. A dominance-based stepwise approach for sensor placement optimization Applied Soft Computing Journal. 28: 466-482. DOI: 10.1016/J.Asoc.2014.11.051 |
0.35 |
|
| 2015 |
Vellasques E, Sabourin R, Granger E. A dual-purpose memory approach for dynamic particle swarm optimization of recurrent problems Studies in Computational Intelligence. 621: 367-389. DOI: 10.1007/978-3-319-26450-9_14 |
0.79 |
|
| 2015 |
Bertolini D, Oliveira LS, Sabourin R. Improving writer identification through writer selection Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9423: 168-175. DOI: 10.1007/978-3-319-25751-8_21 |
0.311 |
|
| 2014 |
Cruz RMO, Sabourin R, Cavalcanti GDC. On meta-learning for dynamic ensemble selection Proceedings - International Conference On Pattern Recognition. 1230-1235. DOI: 10.1109/ICPR.2014.221 |
0.368 |
|
| 2014 |
Britto AS, Sabourin R, Oliveira LES. Dynamic selection of classifiers - A comprehensive review Pattern Recognition. 47: 3665-3680. DOI: 10.1016/J.Patcog.2014.05.003 |
0.423 |
|
| 2014 |
Pagano C, Granger E, Sabourin R, Marcialis GL, Roli F. Adaptive ensembles for face recognition in changing video surveillance environments Information Sciences. 286: 75-101. DOI: 10.1016/J.Ins.2014.07.005 |
0.407 |
|
| 2014 |
Eskander GS, Sabourin R, Granger E. A bio-cryptographic system based on offline signature images Information Sciences. 259: 170-191. DOI: 10.1016/J.Ins.2013.09.004 |
0.415 |
|
| 2014 |
Radtke PVW, Granger E, Sabourin R, Gorodnichy DO. Skew-sensitive boolean combination for adaptive ensembles - An application to face recognition in video surveillance Information Fusion. 20: 31-48. DOI: 10.1016/J.Inffus.2013.11.001 |
0.428 |
|
| 2014 |
Cruz RMO, Sabourin R, Cavalcanti GDC. Analyzing dynamic ensemble selection techniques using dissimilarity analysis Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8774: 59-70. |
0.314 |
|
| 2013 |
Eskander GS, Sabourin R, Granger E. Hybrid writer-independent writer-dependent offline signature verification system Iet Biometrics. 2: 169-181. DOI: 10.1049/Iet-Bmt.2013.0024 |
0.371 |
|
| 2013 |
Rabil BS, Tliba S, Granger E, Sabourin R. Securing high resolution grayscale facial captures using a blockwise coevolutionary GA Expert Systems With Applications. 40: 6693-6706. DOI: 10.1016/J.Eswa.2013.06.043 |
0.402 |
|
| 2013 |
Batista L, Badri B, Sabourin R, Thomas M. A classifier fusion system for bearing fault diagnosis Expert Systems With Applications. 40: 6788-6797. DOI: 10.1016/J.Eswa.2013.06.033 |
0.326 |
|
| 2013 |
Vellasques E, Sabourin R, Granger E. DS-DPSO: A dual surrogate approach for intelligent watermarking of bi-tonal document image streams Expert Systems With Applications. 40: 5240-5259. DOI: 10.1016/J.Eswa.2013.03.021 |
0.804 |
|
| 2013 |
Ko AHR, Sabourin R, Gagnon F. Performance of distributed multi-agent multi-state reinforcement spectrum management using different exploration schemes Expert Systems With Applications. 40: 4115-4126. DOI: 10.1016/J.Eswa.2013.01.035 |
0.338 |
|
| 2013 |
Cruz RMO, Cavalcanti GDC, Tsang IR, Sabourin R. Feature representation selection based on Classifier Projection Space and Oracle analysis Expert Systems With Applications. 40: 3813-3827. DOI: 10.1016/J.Eswa.2012.12.096 |
0.468 |
|
| 2013 |
Ko AHR, Sabourin R. Single Classifier-based Multiple Classification Scheme for weak classifiers: An experimental comparison Expert Systems With Applications. 40: 3606-3622. DOI: 10.1016/J.Eswa.2012.12.067 |
0.444 |
|
| 2013 |
Bertolini D, Oliveira LS, Justino E, Sabourin R. Texture-based descriptors for writer identification and verification Expert Systems With Applications. 40: 2069-2080. DOI: 10.1016/J.Eswa.2012.10.016 |
0.436 |
|
| 2013 |
Corriveau G, Guilbault R, Tahan A, Sabourin R. Review of phenotypic diversity formulations for diagnostic tool Applied Soft Computing Journal. 13: 9-26. DOI: 10.1016/J.Asoc.2012.08.046 |
0.404 |
|
| 2013 |
Vellasques E, Sabourin R, Granger E. Fast intelligent watermarking of heterogeneous image streams through mixture modeling of PSO populations Applied Soft Computing Journal. 13: 3130-3148. DOI: 10.1016/J.Asoc.2012.08.040 |
0.796 |
|
| 2013 |
Connolly JF, Granger E, Sabourin R. Dynamic multi-objective evolution of classifier ensembles for video face recognition Applied Soft Computing Journal. 13: 3149-3166. DOI: 10.1016/J.Asoc.2012.08.039 |
0.686 |
|
| 2013 |
Ribas FC, Oliveira LS, Britto AS, Sabourin R. Handwritten digit segmentation: A comparative study International Journal On Document Analysis and Recognition. 16: 127-137. DOI: 10.1007/S10032-012-0185-9 |
0.356 |
|
| 2013 |
Rivard D, Granger E, Sabourin R. Multi-feature extraction and selection in writer-independent off-line signature verification International Journal On Document Analysis and Recognition. 16: 83-103. DOI: 10.1007/S10032-011-0180-6 |
0.444 |
|
| 2013 |
Cavalin PR, Sabourin R, Suen CY. Dynamic selection approaches for multiple classifier systems Neural Computing and Applications. 22: 673-688. DOI: 10.1007/S00521-011-0737-9 |
0.792 |
|
| 2013 |
Eskander GS, Sabourin R, Granger E. A dissimilarity-based approach for biometric fuzzy vaults - Application to handwritten signature images Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8158: 95-102. DOI: 10.1007/978-3-642-41190-8_11 |
0.336 |
|
| 2013 |
Eskander GS, Sabourin R, Granger E. On the dissimilarity representation and prototype selection for signature-based bio-cryptographic systems Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7953: 265-280. DOI: 10.1007/978-3-642-39140-8_18 |
0.323 |
|
| 2013 |
Ko AHR, Sabourin R. Single classifier based multiple classifications Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 7872: 134-145. DOI: 10.1007/978-3-642-38067-9_12 |
0.305 |
|
| 2013 |
Connolly JF, Granger E, Sabourin R. Evolving classifier ensembles using dynamic multi-objective swarm intelligence Icpram 2013 - Proceedings of the 2nd International Conference On Pattern Recognition Applications and Methods. 206-215. |
0.639 |
|
| 2013 |
Eskander GS, Sabourin R, Granger E. Dissimilarity representation for handwritten signature verification Ceur Workshop Proceedings. 1022: 26-30. |
0.326 |
|
| 2012 |
Vriesmann LM, Britto ADS, Oliveira LESD, Sabourin R, Ko AH. Improving a dynamic ensemble selection method based on oracle information International Journal of Innovative Computing and Applications. 4: 184-200. DOI: 10.1504/Ijica.2012.050053 |
0.382 |
|
| 2012 |
Granger E, Khreich W, Sabourin R, Gorodnichy DO. Fusion of biometric systems using Boolean combination: An application to iris-based authentication International Journal of Biometrics. 4: 291-315. DOI: 10.1504/Ijbm.2012.047645 |
0.76 |
|
| 2012 |
Lévesque JC, Durand A, Gagné C, Sabourin R. Multi-objective evolutionary optimization for generating ensembles of classifiers in the ROC space Gecco'12 - Proceedings of the 14th International Conference On Genetic and Evolutionary Computation. 879-886. DOI: 10.1145/2330163.2330285 |
0.315 |
|
| 2012 |
Vellasques E, Sabourin R, Granger E. Gaussian mixture modeling for dynamic particle swarm optimization of recurrent problems Gecco'12 - Proceedings of the 14th International Conference On Genetic and Evolutionary Computation. 73-80. DOI: 10.1145/2330163.2330174 |
0.795 |
|
| 2012 |
Corriveau G, Guilbault R, Tahan A, Sabourin R. Review and study of genotypic diversity measures for real-coded representations Ieee Transactions On Evolutionary Computation. 16: 695-710. DOI: 10.1109/Tevc.2011.2170075 |
0.316 |
|
| 2012 |
Cavalin PR, Sabourin R, Suen CY. LoGID: An adaptive framework combining local and global incremental learning for dynamic selection of ensembles of HMMs Pattern Recognition. 45: 3544-3556. DOI: 10.1016/J.Patcog.2012.02.034 |
0.788 |
|
| 2012 |
Connolly JF, Granger E, Sabourin R. Evolution of heterogeneous ensembles through dynamic particle swarm optimization for video-based face recognition Pattern Recognition. 45: 2460-2477. DOI: 10.1016/J.Patcog.2011.12.016 |
0.687 |
|
| 2012 |
Batista L, Granger E, Sabourin R. Dynamic selection of generative-discriminative ensembles for off-line signature verification Pattern Recognition. 45: 1326-1340. DOI: 10.1016/J.Patcog.2011.10.011 |
0.454 |
|
| 2012 |
Khreich W, Granger E, Miri A, Sabourin R. Adaptive ROC-based ensembles of HMMs applied to anomaly detection Pattern Recognition. 45: 208-230. DOI: 10.1016/J.Patcog.2011.06.014 |
0.8 |
|
| 2012 |
Khreich W, Granger E, Miri A, Sabourin R. A survey of techniques for incremental learning of HMM parameters Information Sciences. 197: 105-130. DOI: 10.1016/J.Ins.2012.02.017 |
0.787 |
|
| 2012 |
Connolly JF, Granger E, Sabourin R. An adaptive classification system for video-based face recognition Information Sciences. 192: 50-70. DOI: 10.1016/J.Ins.2010.02.026 |
0.69 |
|
| 2012 |
Kapp MN, Sabourin R, Maupin P. A dynamic model selection strategy for support vector machine classifiers Applied Soft Computing Journal. 12: 2550-2565. DOI: 10.1016/J.Asoc.2012.04.001 |
0.462 |
|
| 2012 |
Hanusiak RK, Oliveira LS, Justino E, Sabourin R. Writer verification using texture-based features International Journal On Document Analysis and Recognition. 15: 213-226. DOI: 10.1007/S10032-011-0166-4 |
0.432 |
|
| 2012 |
Radtke PVW, Granger E, Sabourin R, Gorodnichy D. Adaptive selection of ensembles for imbalanced class distributions Proceedings - International Conference On Pattern Recognition. 2980-2984. |
0.317 |
|
| 2011 |
Connolly JF, Granger E, Sabourin R. Comparing dynamic PSO algorithms for adapting classifier ensembles in video-based face recognition Ieee Ssci 2011 - Symposium Series On Computational Intelligence - Cibim 2011: 2011 Ieee Workshop On Computational Intelligence in Biometrics and Identity Management. 1-8. DOI: 10.1109/CIBIM.2011.5949226 |
0.644 |
|
| 2011 |
Gorodnichy DO, Dubrofsky E, Hoshino R, Khreich W, Granger E, Sabourin R. Exploring the upper bound performance limit of iris biometrics using score calibration and fusion Ieee Ssci 2011 - Symposium Series On Computational Intelligence - Cibim 2011: 2011 Ieee Workshop On Computational Intelligence in Biometrics and Identity Management. 54-61. DOI: 10.1109/CIBIM.2011.5949213 |
0.743 |
|
| 2011 |
Rabil BS, Sabourin R, Granger E. Impact of watermarking on offline signature verification in intelligent bio-watermarking systems Ieee Ssci 2011 - Symposium Series On Computational Intelligence - Cibim 2011: 2011 Ieee Workshop On Computational Intelligence in Biometrics and Identity Management. 13-20. DOI: 10.1109/CIBIM.2011.5949206 |
0.362 |
|
| 2011 |
Vellasques E, Sabourin R, Granger E. A high throughput system for intelligent watermarking of bi-tonal images Applied Soft Computing Journal. 11: 5215-5229. DOI: 10.1016/J.Asoc.2011.05.038 |
0.8 |
|
| 2011 |
Khreich W, Granger E, Miri A, Sabourin R. Incremental boolean combination of classifiers Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6713: 340-349. DOI: 10.1007/978-3-642-21557-5_36 |
0.749 |
|
| 2011 |
Kapp MN, Sabourin R, Maupin P. A dynamic optimization approach for adaptive incremental learning International Journal of Intelligent Systems. 26: 1101-1124. DOI: 10.1002/Int.20501 |
0.462 |
|
| 2011 |
Rabil BS, Sabourin R, Granger E. Watermarking stack of grayscale face images as dynamic multi-objective optimization problem Advances in Mass Data Analysis of Images and Signals in Medicine, Biotechnology, Chemistry and Food Industry - 6th International Conference, Mda 2011, Proceedings. 63-77. |
0.303 |
|
| 2010 |
Vellasques E, Sabourin R, Granger E. Intelligent watermarking of document images as a dynamic optimization problem Proceedings - 2010 6th International Conference On Intelligent Information Hiding and Multimedia Signal Processing, Iihmsp 2010. 139-142. DOI: 10.1109/IIHMSP.2010.42 |
0.796 |
|
| 2010 |
Rabil BS, Sabourin R, Granger E. Intelligent watermarking with multi-objective Population Based Incremental Learning Proceedings - 2010 6th International Conference On Intelligent Information Hiding and Multimedia Signal Processing, Iihmsp 2010. 131-134. DOI: 10.1109/IIHMSP.2010.40 |
0.306 |
|
| 2010 |
Kapp MN, Sabourin R, Maupin P. Adaptive incremental learning with an ensemble of support vector machines Proceedings - International Conference On Pattern Recognition. 4048-4051. DOI: 10.1109/ICPR.2010.984 |
0.375 |
|
| 2010 |
Batista L, Granger E, Sabourin R. Applying dissimilarity representation to off-line signature verification Proceedings - International Conference On Pattern Recognition. 1293-1297. DOI: 10.1109/ICPR.2010.322 |
0.319 |
|
| 2010 |
Khreich W, Granger E, Miri A, Sabourin R. Boolean combination of classifiers in the ROC space Proceedings - International Conference On Pattern Recognition. 4299-4303. DOI: 10.1109/ICPR.2010.1045 |
0.777 |
|
| 2010 |
Connolly JF, Granger E, Sabourin R. An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification 2010 Ieee World Congress On Computational Intelligence, Wcci 2010 - 2010 Ieee Congress On Evolutionary Computation, Cec 2010. DOI: 10.1109/CEC.2010.5585941 |
0.628 |
|
| 2010 |
Khreich W, Granger E, Miri A, Sabourin R. On the memory complexity of the forward-backward algorithm Pattern Recognition Letters. 31: 91-99. DOI: 10.1016/J.Patrec.2009.09.023 |
0.738 |
|
| 2010 |
Khreich W, Granger E, Miri A, Sabourin R. Iterative Boolean combination of classifiers in the ROC space: An application to anomaly detection with HMMs Pattern Recognition. 43: 2732-2752. DOI: 10.1016/J.Patcog.2010.03.006 |
0.79 |
|
| 2010 |
Bertolini D, Oliveira LS, Justino E, Sabourin R. Reducing forgeries in writer-independent off-line signature verification through ensemble of classifiers Pattern Recognition. 43: 387-396. DOI: 10.1016/J.Patcog.2009.05.009 |
0.444 |
|
| 2010 |
Batista L, Granger E, Sabourin R. Improving performance of HMM-based off-line signature verification systems through a multi-hypothesis approach International Journal On Document Analysis and Recognition. 13: 33-47. DOI: 10.1007/S10032-009-0101-0 |
0.448 |
|
| 2010 |
Batista L, Granger E, Sabourin R. A multi-classifier system for off-line signature verification based on dissimilarity representation Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5997: 264-273. DOI: 10.1007/978-3-642-12127-2-27 |
0.307 |
|
| 2010 |
Cavalin PR, Sabourin R, Suen CY. Dynamic selection of ensembles of classifiers using contextual information Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5997: 145-154. DOI: 10.1007/978-3-642-12127-2-15 |
0.78 |
|
| 2009 |
Ko AH, Cavalin PR, Sabourin R, de Souza Britto A. 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. Ieee Transactions On Pattern Analysis and Machine Intelligence. 31: 2168-78. PMID 19834139 DOI: 10.1109/Tpami.2008.254 |
0.774 |
|
| 2009 |
Kapp MN, Sabourin R, Maupin P. A PSO-based framework for dynamic SVM model selection Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, Gecco-2009. 1227-1234. DOI: 10.1145/1569901.1570066 |
0.339 |
|
| 2009 |
Radtke PVW, Wong T, Sabourin R. Solution over-fit control in evolutionary multiobjective optimization of pattern classification systems International Journal of Pattern Recognition and Artificial Intelligence. 23: 1107-1127. DOI: 10.1142/S0218001409007466 |
0.412 |
|
| 2009 |
KO AH, SABOURIN R, DE SOUZA BRITTO A. COMPOUND DIVERSITY FUNCTIONS FOR ENSEMBLE SELECTION International Journal of Pattern Recognition and Artificial Intelligence. 23: 659-686. DOI: 10.1142/S021800140900734X |
0.381 |
|
| 2009 |
Vellasques E, Granger E, Sabourin R. Intelligent watermarking systems: A survey Handbook of Pattern Recognition and Computer Vision, Fourth Edition. 687-724. DOI: 10.1142/9789814273398_031 |
0.792 |
|
| 2009 |
Batista L, Granger E, Sabourin R. A multi-hypothesis approach for off-line signature verification with HMMs Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 1315-1319. DOI: 10.1109/ICDAR.2009.5 |
0.33 |
|
| 2009 |
Santos M, Ko A, Oliveira LS, Sabourin R, Koerich AL, Britto AS. Evaluation of different strategies to optimize an HMM-based character recognition system Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 666-670. DOI: 10.1109/ICDAR.2009.230 |
0.694 |
|
| 2009 |
Khreich W, Granger E, Sabourin R, Miri A. Combining Hidden Markov Models for improved anomaly detection Ieee International Conference On Communications. DOI: 10.1109/ICC.2009.5198832 |
0.774 |
|
| 2009 |
Connolly JF, Granger E, Sabourin R. Incremental adaptation of fuzzy ARTMAP neural networks for video-based face classification Ieee Symposium On Computational Intelligence For Security and Defense Applications, Cisda 2009. DOI: 10.1109/CISDA.2009.5356545 |
0.638 |
|
| 2009 |
Khreich W, Granger E, Miri A, Sabourin R. A comparison of techniques for on-line incremental learning of HMM parameters in anomaly detection Ieee Symposium On Computational Intelligence For Security and Defense Applications, Cisda 2009. DOI: 10.1109/CISDA.2009.5356542 |
0.772 |
|
| 2009 |
Bergamini C, Oliveira LS, Koerich AL, Sabourin R. Combining different biometric traits with one-class classification Signal Processing. 89: 2117-2127. DOI: 10.1016/J.Sigpro.2009.04.043 |
0.689 |
|
| 2009 |
Cavalin PR, Sabourin R, Suen CY, Britto AS. Evaluation of incremental learning algorithms for HMM in the recognition of alphanumeric characters Pattern Recognition. 42: 3241-3253. DOI: 10.1016/J.Patcog.2008.10.012 |
0.775 |
|
| 2009 |
Dos Santos EM, Sabourin R, Maupin P. Overfitting cautious selection of classifier ensembles with genetic algorithms Information Fusion. 10: 150-162. DOI: 10.1016/J.Inffus.2008.11.003 |
0.419 |
|
| 2008 |
Oliveira LS, Justino E, Sabourin R, Bortolozzi F. Combining classifiers in the ROC-space for off-line signature verification Journal of Universal Computer Science. 14: 237-251. DOI: 10.3217/Jucs-014-02-0237 |
0.452 |
|
| 2008 |
Granger E, Connolly JF, Sabourin R. A comparison of fuzzy ARTMAP and Gaussian ARTMAP neural networks for incremental learning Proceedings of the International Joint Conference On Neural Networks. 3305-3312. DOI: 10.1109/IJCNN.2008.4634267 |
0.588 |
|
| 2008 |
Bergamini C, Oliveira LS, Koerich AL, Sabourin R. Fusion of biometrie systems using one-class classification Proceedings of the International Joint Conference On Neural Networks. 1308-1313. DOI: 10.1109/IJCNN.2008.4633967 |
0.668 |
|
| 2008 |
Dos Santos EM, Sabourin R, Maupin P. A dynamic overproduce-and-choose strategy for the selection of classifier ensembles Pattern Recognition. 41: 2993-3009. DOI: 10.1016/J.Patcog.2008.03.027 |
0.406 |
|
| 2008 |
Vellasques E, Oliveira LS, Britto AS, Koerich AL, Sabourin R. Filtering segmentation cuts for digit string recognition Pattern Recognition. 41: 3044-3053. DOI: 10.1016/J.Patcog.2008.03.019 |
0.769 |
|
| 2008 |
Ko AHR, Sabourin R, Britto, AS. From dynamic classifier selection to dynamic ensemble selection Pattern Recognition. 41: 1735-1748. DOI: 10.1016/J.Patcog.2007.10.015 |
0.385 |
|
| 2008 |
Connolly JF, Granger E, Sabourin R. Supervised incremental learning with the fuzzy ARTMAP neural network Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 5064: 66-77. DOI: 10.1007/978-3-540-69939-2_7 |
0.58 |
|
| 2007 |
Radtke PVW, Sabourin R, Wong T. Annealing based approach to optimize classification systems Ieee International Conference On Neural Networks - Conference Proceedings. 2616-2620. DOI: 10.1109/IJCNN.2007.4371371 |
0.321 |
|
| 2007 |
Oliveira LS, Justino E, Sabourin R. Off-line signature verification using writer-independent approach Ieee International Conference On Neural Networks - Conference Proceedings. 2539-2544. DOI: 10.1109/IJCNN.2007.4371358 |
0.344 |
|
| 2007 |
Ko AH, Sabourin R, Britto AdS, Oliveira L. Pairwise fusion matrix for combining classifiers Pattern Recognition. 40: 2198-2210. DOI: 10.1016/J.Patcog.2007.01.031 |
0.623 |
|
| 2007 |
Kapp MN, Freitas COdA, Sabourin R. Methodology for the design of NN-based month-word recognizers written on Brazilian bank checks Image and Vision Computing. 25: 40-49. DOI: 10.1016/J.Imavis.2006.01.005 |
0.414 |
|
| 2007 |
Côté P, Parrott L, Sabourin R. Multi-objective optimization of an ecological assembly model Ecological Informatics. 2: 23-31. DOI: 10.1016/J.Ecoinf.2007.02.001 |
0.306 |
|
| 2007 |
Ko AH, Sabourin R, Britto AdS. Ensemble of HMM classifiers based on the clustering validity index for a handwritten numeral recognizer Pattern Analysis and Applications. 12: 21-35. DOI: 10.1007/S10044-007-0094-6 |
0.416 |
|
| 2006 |
Oliveira LS, Morita M, Sabourin R. Feature selection for ensembles applied to handwriting recognition International Journal On Document Analysis and Recognition. 8: 262-279. DOI: 10.1007/S10032-005-0013-6 |
0.78 |
|
| 2006 |
Dos Santos EM, Sabourin R, Maupin P. Single and multi-objective genetic algorithms for the selection of ensemble of classifiers Ieee International Conference On Neural Networks - Conference Proceedings. 3070-3077. |
0.308 |
|
| 2006 |
Radtke PVW, Wong T, Sabourin R. An evaluation of over-fit control strategies for multi-objective evolutionary optimization Ieee International Conference On Neural Networks - Conference Proceedings. 3327-3334. |
0.311 |
|
| 2005 |
Koerich AL, Sabourin R, Suen CY. Recognition and verification of unconstrained handwritten words. Ieee Transactions On Pattern Analysis and Machine Intelligence. 27: 1509-22. PMID 16237988 DOI: 10.1109/Tpami.2005.207 |
0.677 |
|
| 2005 |
Milgram J, Sabourin R, Cheriet M. Combining Model-based and Discriminative Approaches in a Modular Two-stage Classification System: Application to Isolated Handwritten Digit Recognition Elcvia Electronic Letters On Computer Vision and Image Analysis. 5: 1. DOI: 10.5565/Rev/Elcvia.92 |
0.429 |
|
| 2005 |
Morita M, Oliveira LS, Sabourin R. Generating ensemble of classifiers through unsupervised feature selection Ieee Latin America Transactions. 3: 447-453. DOI: 10.1109/TLA.2005.1642441 |
0.338 |
|
| 2005 |
Radtke PVW, Sabourin R, Wong T. Intelligent feature extraction for ensemble of classifiers Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 2005: 866-870. DOI: 10.1109/ICDAR.2005.146 |
0.327 |
|
| 2005 |
Nassif N, Kajl S, Sabourin R. Optimization of HVAC control system strategy using two-objective genetic algorithm Hvac and R Research. 11: 459-486. DOI: 10.1080/10789669.2005.10391148 |
0.332 |
|
| 2005 |
Justino EJR, Bortolozzi F, Sabourin R. A comparison of SVM and HMM classifiers in the off-line signature verification Pattern Recognition Letters. 26: 1377-1385. DOI: 10.1016/J.Patrec.2004.11.015 |
0.423 |
|
| 2005 |
Radtke PVW, Wong T, Sabourin R. A multi-objective memetic algorithm for intelligent feature extraction Lecture Notes in Computer Science. 3410: 767-781. |
0.301 |
|
| 2005 |
Oliveira LS, Morita M, Sabourin R, Bortolozzi F. Multi-objective genetic algorithms to create ensemble of classifiers Lecture Notes in Computer Science. 3410: 592-606. |
0.342 |
|
| 2004 |
Nassif N, Kajl S, Sabourin R. Two-objective on-line optimization of supervisory control strategy Building Services Engineering Research and Technology. 25: 241-251. DOI: 10.1191/0143624404Bt105Oa |
0.318 |
|
| 2004 |
Freitas COA, Bortolozzi F, Sabourin R. Study of perceptual similarity between different lexicons International Journal of Pattern Recognition and Artificial Intelligence. 18: 1321-1338. DOI: 10.1142/S0218001404003629 |
0.386 |
|
| 2004 |
Koerich AL, Sabourin R, Suen CY. Fast two-level HMM decoding algorithm for large vocabulary handwriting recognition Proceedings - International Workshop On Frontiers in Handwriting Recognition, Iwfhr. 232-237. DOI: 10.1109/IWFHR.2004.42 |
0.65 |
|
| 2004 |
Morita M, Oliveira LS, Sabourin R. Unsupervised feature selection for ensemble of classifiers Proceedings - International Workshop On Frontiers in Handwriting Recognition, Iwfhr. 81-86. DOI: 10.1109/IWFHR.2004.105 |
0.332 |
|
| 2004 |
Milgram J, Sabourin R, Cheriet M. Two-stage classification system combining model-based and discriminative approaches Proceedings - International Conference On Pattern Recognition. 1: 152-155. DOI: 10.1109/ICPR.2004.1334030 |
0.316 |
|
| 2004 |
Nunes CM, Britto AdS, Kaestner CAA, Sabourin R. Feature subset selection using an optimized hill climbing algorithm for handwritten character recognition Lecture Notes in Computer Science. 1018-1025. DOI: 10.1007/978-3-540-27868-9_112 |
0.44 |
|
| 2003 |
Oliveira LS, Sabourin R, Bortolozzi F, Suen CY. A methodology for feature selection using multiobjective genetic algorithms for handwritten digit string recognition International Journal of Pattern Recognition and Artificial Intelligence. 17: 903-929. DOI: 10.1142/S021800140300271X |
0.435 |
|
| 2003 |
Grandidier F, Sabourin R, Suen CY. Integration of contextual information in handwriting recognition systems Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 2003: 1252-1256. DOI: 10.1109/ICDAR.2003.1227858 |
0.783 |
|
| 2003 |
Oliveira LS, Sabourin R, Bortolozzi F, Suen CY. Feature selection for ensembles: A hierarchical multi-objective genetic algorithm approach Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 2003: 676-680. DOI: 10.1109/ICDAR.2003.1227748 |
0.324 |
|
| 2003 |
Morita M, Sabourin R, Bortolozzi F, Suen CY. Unsupervised feature selection using multi-objective genetic algorithms for handwritten word recognition Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 2003: 666-670. DOI: 10.1109/ICDAR.2003.1227746 |
0.307 |
|
| 2003 |
Koerich AL, Sabourin R, Suen CY. Large vocabulary off-line handwriting recognition: A survey Pattern Analysis and Applications. 6: 97-121. DOI: 10.1007/S10044-002-0169-3 |
0.672 |
|
| 2003 |
Koerich AL, Sabourin R, Suen CY. Lexicon-driven HMM decoding for large vocabulary handwriting recognition with multiple character models International Journal On Document Analysis and Recognition. 6: 126-144. DOI: 10.1007/S10032-003-0113-0 |
0.689 |
|
| 2002 |
Oliveira LS, Sabourin R, Bortolozzi F, Suen CY. Automatic recognition of handwritten numerical strings: A Recognition and Verification strategy Ieee Transactions On Pattern Analysis and Machine Intelligence. 24: 1438-1454. DOI: 10.1109/Tpami.2002.1046154 |
0.435 |
|
| 2002 |
Koerich AL, Leydier Y, Sabourin R, Suen CY. A hybrid large vocabulary handwritten word recognition system using neural networks with hidden Markov models Proceedings - International Workshop On Frontiers in Handwriting Recognition, Iwfhr. 99-104. DOI: 10.1109/IWFHR.2002.1030893 |
0.662 |
|
| 2002 |
Koerich AL, Sabourin R, Suen CY. Fast two-level Viterbi search algorithm for unconstrained handwriting recognition Icassp, Ieee International Conference On Acoustics, Speech and Signal Processing - Proceedings. 4. |
0.641 |
|
| 2001 |
Koerich AL, Sabourin R, Suen CY. A distributed scheme for lexicon-driven handwritten word recognition and its application to large vocabulary problems Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 2001: 660-664. DOI: 10.1109/ICDAR.2001.953872 |
0.657 |
|
| 2001 |
Grandidier F, Sabourin R, Gilloux M, Suen CY. An a priori indicator of the discrimination power of discrete hidden Markov models Proceedings of the International Conference On Document Analysis and Recognition, Icdar. 2001: 350-354. DOI: 10.1109/ICDAR.2001.953812 |
0.781 |
|
| 2001 |
Koerich AL, Sabourin R, Suen CY. A timeñlength constrained level building algorithm for large vocabulary handwritten word recognition Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2013: 127-136. |
0.676 |
|
| 2001 |
Britto AdS, Sabourin R, Bortolozzi F, Suen CY. An enhanced HMM topology in an LBA framework for the recognition of handwritten numeral strings Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2013: 105-114. |
0.304 |
|
| 2000 |
Morita ME, Letheuer E, El Yacoubi A, Bortolozzi F, Sabourin R. Recognition of handwritten dates on bank checks using an HMM approach Brazilian Symposium of Computer Graphic and Image Processing. 2000: 113-120. DOI: 10.1109/SIBGRA.2000.883903 |
0.757 |
|
| 1999 |
El-Yacoubi A, Gilloux M, Sabourin R, Suen CY. An HMM-based approach for off-line unconstrained handwritten word modeling and recognition Ieee Transactions On Pattern Analysis and Machine Intelligence. 21: 752-760. DOI: 10.1109/34.784288 |
0.419 |
|
| 1997 |
Murshed NA, Sabourin R, Bortolozzi F. A cognitive approach to off-line signature verification International Journal of Pattern Recognition and Artificial Intelligence. 11: 801-824. DOI: 10.1142/S0218001497000366 |
0.394 |
|
| 1997 |
Murshed NA, Bortolozzi F, Sabourin R. Binary image compression using identity mapping backpropagation neural network Electronic Imaging. 3030: 29-35. DOI: 10.1117/12.269779 |
0.368 |
|
| 1997 |
Sabourin R. Off-line signature verification by local granulometric size distributions Ieee Transactions On Pattern Analysis and Machine Intelligence. 19: 976-988. DOI: 10.1109/34.615447 |
0.354 |
|
| 1997 |
E1-Yacoubi A, Gilloux M, Sabourin R, Suen CY. Objective evaluation of the discriminant power of features in an HMM-based word recognition system Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1339: 60-73. DOI: 10.1007/3-540-63791-5_4 |
0.399 |
|
| 1997 |
Santos JEBD, Bortolozzi F, Sabourin R. A Simple Methodology to Bankcheck Segmentation Lecture Notes in Computer Science. 334-343. DOI: 10.1007/3-540-63791-5_26 |
0.328 |
|
| 1997 |
Simon C, Levrat E, Sabourin R, Bremont J. A fuzzy perception for off-line handwritten signature verification Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1339: 261-272. DOI: 10.1007/3-540-63791-5_20 |
0.337 |
|
| 1996 |
Murshed NA, Bortolozzi F, Sabourin R. Classification of cancerous cells based on the one-class problem approach Proceedings of Spie. 2760: 487-494. DOI: 10.1117/12.235938 |
0.354 |
|
| 1996 |
Drouhard JP, Sabourin R, Godbout M. A neural network approach to off-line signature verification using directional PDF Pattern Recognition. 29: 415-424. DOI: 10.1016/0031-3203(95)00092-5 |
0.338 |
|
| 1994 |
SABOURIN R, PLAMONDON R, BEAUMIER L. STRUCTURAL INTERPRETATION OF HANDWRITTEN SIGNATURE IMAGES International Journal of Pattern Recognition and Artificial Intelligence. 8: 709-748. DOI: 10.1142/S0218001494000383 |
0.362 |
|
| Show low-probability matches. |