{"id":189,"date":"2017-09-06T15:21:59","date_gmt":"2017-09-06T18:21:59","guid":{"rendered":"http:\/\/web.inf.ufpr.br\/luizoliveira\/?page_id=189"},"modified":"2024-02-19T15:22:13","modified_gmt":"2024-02-19T18:22:13","slug":"journal-papers","status":"publish","type":"page","link":"https:\/\/web.inf.ufpr.br\/luizoliveira\/publications\/journal-papers\/","title":{"rendered":"Journals"},"content":{"rendered":"\n
    \n
  1. Ceschin, F., Gomes, H., Botacin, M., Bifet, A., Pfahringer, B., Oliveira, L. S<\/strong>., Gregio, A., Machine Learning (In) Security: A Stream of Problems, ACM Digital Threats: Research and Practice, accepted for publication [pdf<\/a>]<\/li>\n\n\n\n
  2. Ensina, L., Oliveira, L.S.<\/strong>, Cruz, R., Cavalcanti, G., Fault distance estimation for transmission lines with dynamic regressor selection, Neural Computing and Applications, 34:1741-1759, 2024 [pdf<\/a>]<\/li>\n\n\n\n
  3. Furtado D.P., Vieira E.A., Nascimento W.F., Inagaki K.Y., Bleuel J., Alves M., Longo G.O., Oliveira L.S.  <\/strong>#DeOlhoNosCorais: a polygonal annotated dataset to optimize coral monitoring. PeerJ<\/em>11:e16219, 2023 [link<\/a>].<\/li>\n\n\n\n
  4. Matos J., Oliveira, L. S.<\/strong>, Britto Jr., A, Koerich, A., Large-Margin Representation Learning for Texture Classification, Pattern Recognition Letters, 170:39-47, 2023 [pdf<\/a>].<\/li>\n\n\n\n
  5. Monteiro Jr, M., Britto Jr, A., Barddal, J., Oliveira, L. S<\/strong>., Sabourin, R., Exploring Diversity in Data Complexity and Classifier Decision Spaces for Pool Generation, Information Fusion, 89, 2023 [pdf<\/a>]. <\/li>\n\n\n\n
  6. Ceschin, F., Botacin, M., Gomes, H., Pinage, F., Oliveira, L. S<\/strong>., Gregio, A., Fast & Furious: On the Modelling of Malware Detection as an Evolving Data Stream, Expert Systems with Applications, 212, 2023 [pdf<\/a>]<\/li>\n\n\n\n
  7. Costa, Y. M. G.; <\/strong>Teixeira, L. O.; Silva JR., S. A.; Bertolini, D.; Pereira, R. M.; Britto JR., A. S.; Oliveira, L. S.<\/strong>; Cavalcanti, G. D. C. COVID-19 detection on chest X-ray and CT scan:a review of the top-100 most cited papers. Sensors, 22<\/em>(19), 7303, 2022. [pdf<\/a>]<\/li>\n\n\n\n
  8. V. M. Ara\u00fajo, A. S. Britto Jr, L. S Oliveira<\/strong>, A. L. Koerich, Two-view fine-grained classification of plant species, Neurocomputing, 466:427-441, 2022 [pdf<\/a>]<\/li>\n\n\n\n
  9. L. Zanlorenzi, R. Laroca, E. Luz, A. S. Britto Jr, L. S. Oliveira<\/strong>, D. Menotti, Ocular Recognition Databases and Competitions: A Survey, Artificial Intelligence Review,55:129-180, 2022 [pdf<\/a>].<\/li>\n\n\n\n
  10. L. Teixeira, R. Pereira, D. Bertolini, L. S. Oliveira<\/strong>, L. Nanni, G. Cavalcanti, Y. Costa, Impact of lung segmentation on the Diagnosis and Explanation of covid-19 in chest x-ray images, Sensors 21(21), 7116, 2021. [pdf<\/a>]<\/li>\n\n\n\n
  11. R. Fragoso, G. Cavalcanti, R. Pinheiro, L. S Oliveira<\/strong>, Dynamic selection and combination of one-class classifiers for multi-class classification, Knowledge-Based Systems, 228, 2021 [pdf<\/a>]<\/li>\n\n\n\n
  12. M. M. Moura, L. S. Oliveira<\/strong>, C. Sanquetta,  A. Bastos, M. Mohan, A. P. Dalla Corte, Towards Amazon Forest Restoration: Automatic Detection of Species from UAV Imagery, Remote Sensing, 13(13):1-15, 2021 [pdf<\/a>]<\/li>\n\n\n\n
  13. G. Z. Felipe, J. N. Zanoni, C. Sierakowski, G. Bossolani, S. Souza, F. Flores, L. S. Oliveira<\/strong>, R. Pereira, Y. Costa, Automatic Chronic Degenerative Diseases Identification Using Enteric Nervous System Images, Neural Computing and Applications, 33, 2021. [pdf<\/a>].<\/li>\n\n\n\n
  14. Martins, J., Oliveira, L. S.<\/strong>, Weingaertner, D., Barison, A., Oliveira, G., Li\u00e3o, L., A Database for Automatic Classification of Gender in Araucaria Angustifolia<\/em> plants, Soft Computing, 25(7), 5503-5517, 2021 [pdf<\/a>].<\/li>\n\n\n\n
  15. Matos, J., Ataky, S., Britto, Jr, A., Oliveira, L. S.<\/strong>, Koerich, A., Machine Learning Methods for Histopathological Image Analysis: A Review, Electronics, 10(5):562-604, 2021 [pdf<\/a>].<\/li>\n\n\n\n
  16. Maruyama, T., Oliveira, L. S.<\/strong>, Britto Jr, A., Sabourin, R., Intrapersonal Parameter Optimization for Offline Handwritten Signature Augmentation, IEEE Transactions on Information Forensics and Security, 16:1335-1350, 2021 [pdf<\/a>]<\/li>\n\n\n\n
  17. Moura, T., Cavalcanti, G., Oliveira, L. S<\/strong>., MINE: A Framework for Dynamic Regressor Selection, Information Sciences, 543:157-179, 2021 [pdf<\/a>]<\/li>\n\n\n\n
  18. Hochuli, A., Britto Jr, A., Saji, D., Saavedra, J., Sabourin, R., Oliveira L. S.<\/strong>, A Comprehensive Comparison of End-to-End Approaches for Handwritten Digit String Recognition, Expert Systems with Applications, 165, 2021 [pdf<\/a>].<\/li>\n\n\n\n
  19. Souza, D. V., Santos, J. X., Vieira, H. C., Niade, T. L, Nisgoski, S., Oliveira, L. S<\/strong>., An automatic recognition system of Brazilian flora species based on textural feature of macroscopic images of wood, Wood Science and Technology, 54:1065-1090, 2020 [pdf<\/a>].<\/li>\n\n\n\n
  20. Silva, R., Britto Jr., A., Enembreck, F., Sabourin, R., Oliveira, L. S. <\/strong>Selecting and combining classifiers based on Centrality Measures,International Journal on Artificial Intelligence Tools, 29(3-4):1-25. 2020 [pdf<\/a>].<\/li>\n\n\n\n
  21. Costa, Y., Bertolini, D.,  Britto Jr, A. S., Cavalcanti, G., Oliveira, L. S<\/strong>., The Dissimilarity Approach: a review, Artificial Intelligence Review, 53(4):2783-2808, 2020 [pdf<\/a>]<\/li>\n\n\n\n
  22. Silva, R., Britto Jr., A., Enembreck, F., Sabourin, R., Oliveira, L. S.<\/strong>, CSBF: A Static Ensemble Fusion Method based on the CentralityScore of Complex Networks, Computational Intelligence, 36(2):522-556, 2020. [pdf<\/a>]<\/li>\n\n\n\n
  23. Hafemann, L.G., Sabourin, R., Oliveira, L. S.<\/strong>,Meta-learning for fast classifier adaptation to new users of Signature Verification systems, IEEE Trans. on Information Forensics and Security, 15:1735-1745, 2020 [pdf<\/a>]<\/li>\n\n\n\n
  24. Ferreira, T. B., Buiar, J. A., Fernandes, M. A., Pimentel, A. R., Oliveira, L. S,<\/strong> Rules for forming collaborative groups using automatic detection of personality traits, Brazilian Journal of Computers in Education, 28:373-296, 2020.<\/li>\n\n\n\n
  25. Matsushita, G., Sugi, A. H, Costa, Y., Gomez, A., Cunha, C., Oliveira, L. S<\/strong>., Automatic dopamine release identification using convolutional neural network, Computers in Biology and Medicine, 114, 2019 [pdf<\/a>]<\/li>\n\n\n\n
  26. Hafemann, L.G., Sabourin, R., Oliveira, L. S.<\/strong>, Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification, IEEE Trans. on Information Forensics and Security, 14(8):2153-2166, 2019 [pdf<\/a>]<\/li>\n\n\n\n
  27. P.J. Sudharshan, P. J,  Petitjean, C., Spanhol, F., Oliveira, L.S.<\/strong>, Heutte, L., Honeine, P., Multiple instance learning for histopathological breast cancer image classification, Expert Systems With Applications, 117:103-111, 2019. [pdf<\/a>]<\/li>\n\n\n\n
  28. F. Ceschin, F. Pinag\u00e9, M. Castilho, D. Menotti, L. S. Oliveira<\/strong>, A. Gr\u00e9gio, The Need for Speed: An Analysis of Brazilian Malware Classifers, IEEE Security and Privacy, 16(6):31-41,2018. [pdf<\/a>]<\/li>\n\n\n\n
  29. Zottesso, R, Costa, Y., Bertolini, D.,  Oliveira, L. S<\/strong>.,Bird species identification using spectrogram and dissimilarity approach, Ecological Informatics, 48:187-197, 2018. [pdf<\/a>]<\/li>\n\n\n\n
  30. Viegas, E., Santin, A., Oliveira, L. S<\/strong>. Fran\u00e7a, A., Jasinski, R., Pedroni, V., A Reliable and Energy-Efficient Classifier Combination Scheme for Intrusion Detection in Embedded Systems, Computers & Security,78:16-32, 2018 [pdf<\/a>]<\/li>\n\n\n\n
  31. Hafemann, L.G., Sabourin, R., Oliveira, L. S.<\/strong>, Fixed-sized representation learning from Offline Handwritten Signatures of different sizes, International Journal of Document Analysis and Recognition (IJDAR), 21:219-232, 2018 [pdf<\/a>]<\/li>\n\n\n\n
  32. Maruyama, T., Oliveira, L. S<\/strong>., Britto Jr, Nisgoski, S., Automatic Classification of Native Wood Charcoal, Ecological Informatics, 48:1-7, 2018. [pdf<\/a>]<\/li>\n\n\n\n
  33. Almeida, P., Oliveira, L. S<\/strong>., Britto Jr., A., Sabourin, R., Adapting Dynamic Classifier Selection for Concept Drift, Expert Systems with Applications, 104:67-85, 2018. [pdf<\/a>]<\/li>\n\n\n\n
  34. Hochuli, A., Oliveira, L. S<\/strong>., Britto Jr., A., Sabourin, R.,  Handwritten Digits Segmentation: Is it still necessary?, Pattern Recognition, 78:1-11, 2018. [pdf<\/a>]<\/li>\n\n\n\n
  35. Luz, E., Moreira, G., Oliveira, L. S<\/strong>., Schwartz, W., Menotti, D., Learning Deep Off-the-Person Heart Biometrics Representation, IEEE Trans. on Information Forensics and Security, 13(5):1258-1270, 2018. [pdf<\/a>]<\/li>\n\n\n\n
  36. Brun, A., Britto Jr, A. S., Oliveira, L. S., <\/strong>Enembreck, F., Sabourin, R. A Framework for Dynamic Classifier Selection oriented by the Classification Problem Difficulty, Pattern Recognition, 76:175-190, 2018 [pdf<\/a>].<\/li>\n\n\n\n
  37. Viegas E., Santin, A., Oliveira, L. S.<\/strong>, Toward a Reliable Anomaly-Based Intrusion Detection in Real-World Environments, Computer Networks, 127:200-216, 2017 [pdf<\/a>]<\/li>\n\n\n\n
  38. Hafemann, L.G., Sabourin, R., Oliveira, L. S.<\/strong>, Learning Features for Offline Handwritten Signature Verification using Deep Convolutional Neural Networks, Pattern Recognition, 70:163-176, 2017 [pdf<\/a>]<\/li>\n\n\n\n
  39. Furlaneto, D.,  Oliveira, L. S<\/strong>., Menotti, D., Cavalcanti, G., Bias effect on predicting market trends with EMD, Expert Systems with Applications, 82:91-26, 2017 [pdf<\/a>]<\/li>\n\n\n\n
  40. Costa, Y. M. G., Oliveira, L. S<\/strong>. Silla Jr., C. N., An Evaluation of Convolutional Neural Networks for Music Classification Using Spectrogram, Applied Soft Computing, 52(1):28-38, 2017. [pdf<\/a>]<\/li>\n\n\n\n
  41. Viegas, E., Santin, A., Fran\u00e7a, A., Jasinski, R., Pedroni, V., Oliveira, L. S<\/strong>., Towards an Energy-Efficient Anomaly-Based Intrusion Detection Engine for Embedded Systems, IEEE Transactions on Computers, (TOC), 66(1):163-177, 2017.  [pdf<\/a>].<\/li>\n\n\n\n
  42. Spanhol, F., Oliveira, L. S<\/strong>., Petitjean, C., Heutte, L., A Dataset for Breast Cancer Histopathological Image Classification, IEEE Transactions on Biomedical Engineering (TBME), 63(7):1455-1462, 2016 [pdf<\/a>].<\/li>\n\n\n\n
  43. Cavalcanti G., Oliveira, L. S, <\/strong>Moura T. M., Carvalho G., Combining Diversity Measures for Ensemble Pruning, Pattern Recognition Letters, 74:38-45, 2016 [pdf<\/a>]<\/li>\n\n\n\n
  44. Almeida, P., Oliveira, L. S.<\/strong>, Britto Jr, A., S., Silva Jr, E., Koerich,A., PKLot \u2013 A Robust dataset for parking lot classification, Expert Systems with Applications, 42(11):4937-4949, 2015. [pdf<\/a>]<\/li>\n\n\n\n
  45. Martins, J., Oliveira, L. S.<\/strong>, Britto Jr, A., S., Sabourin, R., Forest Species Recognition based on Dynamic Classifier Selection and Dissimilarity Feature Vector Representation, Machine Vision and Applications, 26(2):279-293, 2015. [pdf]<\/a><\/li>\n\n\n\n
  46. Climent, J. and Oliveira L. S.<\/strong>, A New Algorithm for Number of Holes Attribute Filtering of Grey-level Images, Pattern Recognition Letters, 53(1):24-30, 2015.[pdf]<\/a><\/li>\n\n\n\n
  47. Britto Jr. A., Sabourin, R., Oliveira, L. S,<\/strong> Dynamic Selection of Classifiers \u2013 A Comprehensive Review, Pattern Recognition, 47(11):3665-3680, 2014. pdf<\/a><\/li>\n\n\n\n
  48. Paula Filho, P. L., Oliveira, L. S.<\/strong>, Nisgoski, S., Britto Jr. A. S., Forest Species Recognition using Macroscopic Images, Machine Vision and Applications, 25(4):1019-1031, 2014. pdf<\/a><\/li>\n\n\n\n
  49. Olivo, C., Santin, A., Oliveira, L. S.<\/strong>, Obtaining the Threat Model for Email Phishing, Applied Soft Computing, 13(12):4841-4848, 2013. pdf<\/a><\/li>\n\n\n\n
  50. Ribas, F. C., Oliveira, L. S.<\/strong>, Britto Jr., A. S., Sabourin, R., Handwritten Digit Segmentation: A Comparative Study, International Journal of Document Analysis and Recognition, 16(2):127-137, 2013 . pdf<\/a><\/li>\n\n\n\n
  51. Martins, J., Oliveira, L. S.<\/strong>, Nisgoski, S., Sabourin, R., A Database for Automatic Classification of Forest Species, Machine Vision and Applications, 24(3):567-578, 2013. pdf<\/a><\/li>\n\n\n\n
  52. Oliveira Jr., W.,Oliveira, L. S.<\/strong>, Justino, E., Comparing Compression Models for Authorship Attribution, Forensic Science International, 228(1-3):100-104, 2013. pdf<\/a>.<\/li>\n\n\n\n
  53. Silva, H.,Oliveira, L. S.<\/strong>, Britto Jr, A. S., Koerich, A. L., Network Infrastructure Design with a Multilevel Algorithm, Expert Systems With Applications, 40(9):3471-3480, 2013. pdf<\/a><\/li>\n\n\n\n
  54. Bertolini, D.,Oliveira, L. S.<\/strong>, Justino, E., Sabourin, R., Texture-based Descriptors for Writer Identification and Verification, Expert Systems With Applications, 40(6):2069-2080, 2013. pdf<\/a><\/li>\n\n\n\n
  55. Zavaschi, T., Britto, Jr. A.S., Oliveira, L. S.,<\/strong> Koerich, A., Fusion of Feature Sets and Classifiers for Facial Expression Recognition, Expert Systems with Applications, 40(2), 646-655, 2013 pdf<\/a><\/li>\n\n\n\n
  56. Vriesmann, L., Britto Jr., A., Oliveira, L. S.<\/strong>, Sabourin, R., Ko, A., Improving a Dynamic Ensemble Selection Method based on Oracle Information, International Journal of Innovative Computing and Applications, 4(3-4):184-200, 2012. pdf<\/a><\/li>\n\n\n\n
  57. Hanusiak, R. K., Justino, E., Oliviera, L. S.<\/strong>, Sabourin, R. Writer Verification Using Texture-based Features, International Journal of Document Analysis and Recognition, 15(3):213-226, 2012. pdf<\/a><\/li>\n\n\n\n
  58. Costa Y., Oliveira, L. S.,<\/strong> Koerich, A. L., Gouyon, F., Martins, J. Music Genre Classification Using LBP Texture Features, Signal Processing, 92(11):2723-2737, 2012. pdf<\/a><\/li>\n\n\n\n
  59. Oliveira, L. S.<\/strong>, Mansano, M., Koerich, A., Britto A., Selecting 2DPCA Coefficients for Face and Facial Expression Recognition, IEEE Computing in Science and Engineering, 13(3):9-13, 2011. pdf<\/a><\/li>\n\n\n\n
  60. Rios, I., Britto Jr., A. S., Koerich, A., Oliveira, L. S.<\/strong>, An OCR Free Method for Word Spotting in Printed Documents: The Evaluation of Different Feature Sets, Journal of Universal Computer Science, 17(1):48-63, 2011.<\/li>\n\n\n\n
  61. Hanusisak R. K., Justino, E., Oliviera, L. S.<\/strong>, Sabourin, R. Identifica\u00e7\u00e3o da Autoria de Manuscritos com Base em Atributos Gen\u00e9ticos e Gen\u00e9ricos da Escrita, Revista de Inform\u00e1tica Te\u00f3rica e Aplicada, 17(2):193-209, 2010 link<\/a> (in Portuguese).<\/li>\n\n\n\n
  62. Bertolini, D.,Oliveira, L. S.<\/strong>, Justino, E., Sabourin, R., Reducing Forgeries in Writer-Independent Off-Line Signature Verification Through Ensemble of Classifiers, Pattern Recognition, 43(1):387-396, 2010. pdf<\/a><\/li>\n\n\n\n
  63. Bergamini, C. M., Oliveira, L. S.<\/strong>, Koerich, A. L., Sabourin, R., Combining different biometric traits with one-class classification, Signal Processing, 89(11):2117-2127, 2009. pdf<\/a><\/li>\n\n\n\n
  64. Pavelec, D., Oliveira, L. S.<\/strong>, Justino, E., Batista L. V., Using Conjunctions and Adverbs for Author Verification. Journal of Universal Computer Science (JUCS), 14(18):2967-2981, 2008. pdf<\/a><\/li>\n\n\n\n
  65. Abu Hana, R., Freitas, C., Oliveira, L. S.<\/strong>, Bortolozzi, F., Crime Scene Classification (2D, 3D, Stereoscopic Projection) and Classification, Journal of Universal Computer Science (JUCS), 14(18):2953-2966, 2008. pdf<\/a><\/li>\n\n\n\n
  66. Oliveira, L. S.<\/strong>, Cavalin, P., Britto Jr., A., Koerich, A., Inspe\u00e7\u00e3o Autom\u00e1rica de Defeitos em Madeira Pinus usando Vis\u00e3o Computacional. Revista de Inform\u00e1tica Te\u00f3rica e Aplicada, 15(2):204-217, 2008. (in Portuguese) pdf<\/a><\/li>\n\n\n\n
  67. Vellasques, E., Oliveira, L. S.<\/strong>, Britto Jr., A., Koerich, A., Sabourin, R., Filtering Segmentation Cuts for Digit String Recognition, Pattern Recognition, 41(10):3044-3053, 2008. pdf<\/a><\/li>\n\n\n\n
  68. Freitras, C., Oliveira, L. S.<\/strong>, Aires, S., Bortolozzi, F., Zoning and Metaclasses for Character Recognition, Journal of Universal Computer Science (JUCS), 14(2):211-223, 2008. pdf<\/a><\/li>\n\n\n\n
  69. Oliveira, L. S<\/strong>., Justino, E., Sabourin, R., Bortolozzi, F., Combining Classifiers in the ROC Space for Off-line Signature Verification, Journal of Universal Computer Science (JUCS), 14(2):237-251, 2008. pdf<\/a><\/li>\n\n\n\n
  70. Pavelec, D., Justino, E., Oliveira, L. S.<\/strong>, Author Identification Using Stylometric Features, Ibero-American Journal of Artificial Intelligence, 11(36):59-65, 2007. pdf<\/a><\/li>\n\n\n\n
  71. Granger, E., Henniges, P., Sabourin, R., Oliveira, L. S.<\/strong>, Supervised Learning of Fuzzy ARTMAP Neural Networks Through Particle Swarm Optimisation, Journal of Pattern Recognition Research (JPRR), 2(1):27-60, 2007. pdf<\/a><\/li>\n\n\n\n
  72. Ko A., Sabourin R., Britto Jr. A., Oliveira L. S.<\/strong>, Pairwise Fusion Matrix for Combining Classifiers. Pattern Recognition, 40(8):2198-2210, 2007. pdf<\/a><\/li>\n\n\n\n
  73. Freitas C., Oliveira L. S.<\/strong>, Aires S., Bortolozzi F., Handwritten Character Recognition Using Non-Symmetrical Perceptual Zoning, International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), 21(1):135-155, 2007. pdf<\/a><\/li>\n\n\n\n
  74. Justino E., Oliveira L. S.<\/strong>, Protocolo para execu\u00e7\u00e3o de mandato de busca e apreens\u00e3o em cen\u00e1rios de crimes digitais, Revista \u00c2mbito Jur\u00eddico, 35:1-7, 2007. (in Portuguese) online<\/a><\/li>\n\n\n\n
  75. Oliveira L. S.<\/strong>, Morita M., and Sabourin R., Feature Selection for Ensembles Applied to Handwriting Recognition,International Journal on Document Analysis and Recognition (IJDAR),18(4):262-279, 2006. pdf<\/a><\/li>\n\n\n\n
  76. Justino E., Oliveira L. S.<\/strong>, Freitas C., Reconstructing Shredded Documents Through Feature Matching, Forensic Science International, 160(2-3):140-147, 2006. pdf<\/a><\/li>\n\n\n\n
  77. Justino E., Freitas C., Oliveira L. S.<\/strong>, T\u00e9cnicas forenses nos crimes de falsidade documental: per\u00edcias para determina\u00e7\u00e3o da contemporaneidade de tintas de caneta, Revista Brasileira de Ci\u00eancias Criminais, 14(59):325-345, 2006. (in Portuguese)<\/li>\n\n\n\n
  78. Morita M., Oliveira L. S.<\/strong>, and Sabourin R., Gera\u00e7\u00e3o Autom\u00e1tica de Conjuntos de Classificadores Atrav\u00e9s da Sele\u00e7\u00e3o de Caracter\u00edsticas n\u00e3o Supervisionada, IEEE Latin America Transactions, 3(5):50-56, 2005, (in Portuguese). pdf<\/a><\/li>\n\n\n\n
  79. Justino E., Oliveira L. S.<\/strong>, Freitas C., Documentoscopia em Documentos Questionados Degradados,Revista \u00c2mbito Jur\u00eddico, 8(22):1-10, 2005, (in Portuguese). online<\/a><\/li>\n\n\n\n
  80. Oliveira L. S.<\/strong>, Sabourin R., Bortolozzi F., Suen C.Y. A Methodology for Feature Selection using Multi-Objective Genetic Algorithms for Handwritten Digit String Recognition, International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), 17(6):903-930, 2003. pdf<\/a><\/li>\n\n\n\n
  81. Oliveira L. S.<\/strong>, Sabourin R., Bortolozzi F., Suen C.Y. Impacts of Verification on a Numeral String Recognition System, Pattern Recognition Letters, 24(7):1023-1031, 2003. pdf<\/a><\/li>\n\n\n\n
  82. Oliveira L. S.<\/strong>, Sabourin R., Bortolozzi F., Suen C.Y. Automatic Recognition of Handwritten Numerical Strings: A Recognition and Verification Strategy, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 24(11):1438-1454, 2002<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":18,"featured_media":0,"parent":65,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-189","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/pages\/189","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/users\/18"}],"replies":[{"embeddable":true,"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/comments?post=189"}],"version-history":[{"count":89,"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/pages\/189\/revisions"}],"predecessor-version":[{"id":757,"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/pages\/189\/revisions\/757"}],"up":[{"embeddable":true,"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/pages\/65"}],"wp:attachment":[{"href":"https:\/\/web.inf.ufpr.br\/luizoliveira\/wp-json\/wp\/v2\/media?parent=189"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}