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Benchmark of Different Gradient Descents in OCR Cover

Benchmark of Different Gradient Descents in OCR

Cybernetics and Information Technologies
Volume 14 (2014): Issue 2 (June 2014)
By: Marjan Kuchaki Rafsanjani and  Masoud Pourshaban  
Open Access
|Jul 2014

References

  1. 1. Broumandnia, A., J. Shanbehzadeh. Fast Zernike Wavelet Moments for Farsi Character Recognition. - Image and Vision Computing, Vol. 25, 2007, 717-726.10.1016/j.imavis.2006.05.014
    Search in Google Scholar
  2. 2. Morita, M. E., E. Lethelier, A. E. Yacoubi, F. Bortolozzi, R. Sabourin, P. Pontifícia. Recognition of Handwritten Dates on Bankchecks Using an HMM Approach. - In: 13th Brazilian Symposium on Computer Graphics and Image Processing, Gramado, Brazil, 2000.
    Search in Google Scholar
  3. 3. Pan, X., X. Ye, S. Zhang. A Hybrid Method for Robust Car Plate Character Recognition. -Engineering Applications of Artificial Intelligence, Vol. 18, 2005, No 8, 963-972.10.1016/j.engappai.2005.03.011
    Search in Google Scholar
  4. 4. AI-A l a w i, R. A Hybrid w-Tuple Neuro-Fuzzy Classifier for Handwritten Numerals Recognition. - In: IEEE International Joint Conference on Neural Networks, Budapest, Hungary, 2004.
    Search in Google Scholar
  5. 5. Amin, A. Recognition of Printed Arabic Text Based on Global Features and Decision Tree Learning Techniques. - Pattern Recognition, Vol. 33, 2000, No 8, 1309-1323.10.1016/S0031-3203(99)00114-4
    Search in Google Scholar
  6. 6. N a g ab hushan, P., R. M. P a i. Modified Region Decomposition Method and Optimal Depth Decision Tree in the Recognition of Non-Uniform Sized Characters - An Experimentation with Kannada Characters. - Pattern Recognition Letters, Vol. 20, 1999, No 14, 1467-1475.10.1016/S0167-8655(99)00058-6
    Search in Google Scholar
  7. 7. C h e o k, A. D., Z. J i a n, E. S. C h n g. Efficient Mobile Phone Chinese Optical Character Recognition Systems by Use of Heuristic Fuzzy Rules and Bigram Markov Language Models. - Applied Soft Computing, Vol. 8, 2008, No 2, 1005-1017.10.1016/j.asoc.2007.02.013
    Search in Google Scholar
  8. 8. Chi, Z., M. Suters, H. Yan. Handwritten Digit Recognition Using Combined ID3-Derived Fuzzy Rules and Markov Chains. - Pattern Recognition, Vol. 29, 1996, No 11, 1821-1833.10.1016/0031-3203(96)00040-4
    Search in Google Scholar
  9. 9. Hanmandlua, M., K. R. M. Mohanb, S. Chakrabortyc, S. Goyald. Unconstrained Handwritten Character Recognition Based on Fuzzy Logic. - Pattern Recognition, Vol. 36, 2003, 603-623.10.1016/S0031-3203(02)00069-9
    Search in Google Scholar
  10. 10. Patil, P. M., T. R. Sontakke. Rotation, Scale and Translation Invariant Handwritten Devanagari Numeral Character Recognition Using General Fuzzy Neural Network. - Pattern Recognition, Vol. 40, 2007, No 7, 2110-2117.10.1016/j.patcog.2006.12.018
    Search in Google Scholar
  11. 11. Goltsev, A., D. Rachkovskij. Combination of the Assembly Neural Network with a Perceptron for Recognition of Handwritten Digits Arranged in Numeral Strings. - Pattern Recognition, Vol. 38, 2005, No 3, 315-322.10.1016/j.patcog.2004.09.001
    Search in Google Scholar
  12. 12. Lauer, F., C. Y. Suen, G. Bloch. A Trainable Feature Extractor for Handwritten Digit Recognition. - Pattern Recognition, Vol. 40, 2007, No 6, 1816-1824.10.1016/j.patcog.2006.10.011
    Search in Google Scholar
  13. 13. Camastra, F. A SVM-Based Cursive Character Recognizer. - Pattern Recognition, Vol. 40, 2007, No 12, 3721-3727.10.1016/j.patcog.2007.03.014
    Search in Google Scholar
  14. 14. Malon, C., S. Uchida, M. Suzuki. Mathematical Symbol Recognition with Support Vector Machines. - Pattern Recognition Letters, Vol. 29, 2008, No 9, 1326-1332.10.1016/j.patrec.2008.02.005
    Search in Google Scholar
  15. 15. Amor, N. B., N. E. B. A mara. Multifont Arabic Character Recognition Using Hough Transform and Hidden Markov Models. - In: Fourth International Symposium on Image and Signal Processing and Analysis, Zagreb, Croatia, 2005.10.1109/ISPA.2005.195424
    Search in Google Scholar
  16. 16. Bunke, H., M. Roth, E. Schukat-Talamazzini. Off-Line Cursive Handwriting Recognition Using Hidden Markov Models. - Pattern Recognition, Vol. 28, 1995, No 1, 399-1413.10.1016/0031-3203(95)00013-P
    Search in Google Scholar
  17. 17. Khorsheed, M. S. Recognising Handwritten Arabic Manuscripts Using a Single Hidden Markov Model. - Pattern Recognition Letters, Vol. 24, 2003, No 14, 2235-2242.10.1016/S0167-8655(03)00050-3
    Search in Google Scholar
  18. 18. Theeramunkong, T., C. Wongtapan. Off-Line Isolated Handwritten Thai OCR Using Island-Based Projection with w-Gram Model and Hidden Markov Models. - Information Processing and Management, Vol. 41, 2005, No 1, 139-160.10.1016/j.ipm.2004.04.011
    Search in Google Scholar
  19. 19. Nagabhushan, P., R. M. Pai. Modified Region Decomposition Method and Optimal Depth Decision Tree in the Recognition of Non-Uniform Sized Characters - An Experimentation with Kannada Characters. - Pattern Recognition Letters, Vol. 20, 1999, No 14, 1467-1475.10.1016/S0167-8655(99)00058-6
    Search in Google Scholar
  20. 20. Ping, Z., C. Lihui. A Novel Feature Extraction Method and Hybrid Tree Classification for Handwritten Numeral Recognition. - Pattern Recognition Letters, Vol. 23, 2002, No 1-3, 4556.10.1016/S0167-8655(01)00088-5
    Search in Google Scholar
  21. 21. Oliveira, L. S., F. Bortolozzi, C. Y. Suen. Automatic Recognition of Handwritten Numerical Strings: A Recognition and Verification Strategy. - IEEE Transactions on Pattern Recognition and Machine Intelligence, Vol. 24, 2001, No 11, 1448-1456.10.1109/TPAMI.2002.1046154
    Search in Google Scholar
  22. 22. Mohiuddin, K. M., J. Mao. A Comprehensive Study of Different Classifiers for HandPrinted Character Recognition. - Pattern Recognition, Practice IV, 1994, 437-448.10.1016/B978-0-444-81892-8.50043-2
    Search in Google Scholar
  23. 23. Koerich, A. L. Unconstrained Handwritten Character Recognition Using Different Classification Strategies. - In: International Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR), 2003.
    Search in Google Scholar
  24. 24. Kim, H., K. K. Kim, C. Y. Suen. Hybrid Schemes of Homogeneous and Heterogeneous Classifiers for Cursive Word Recognition. - In: Proceedings of Seventh International Workshop on Frontiers in Handwritten Recognition, Amsterdam, 2000, 433-442.
    Search in Google Scholar
  25. 25. Al-Omari, F. A., O. Al-Jarrah. Handwritten Indian Numerals Recognition System Using Probabilistic Neural Networks. - Advanced Engineering Informatics, Vol. 18, 2004, No 1, 916.10.1016/j.aei.2004.02.001
    Search in Google Scholar
  26. 26. Pal, U., B. B. Chaudhuri. Indian Script Character Recognition: A Survey. - Pattern Recognition, Vol. 37, 2004, No 9, 1887-1899.10.1016/j.patcog.2004.02.003
    Search in Google Scholar
  27. 27. Hung, K.-Y., R. W. P. L uk, D. S. Yeung, K. F. L. Chung, W. Shu. A Multiple Classifier Approach to Detect Chinese Character Recognition Errors. - Pattern Recognition, Vol. 38, 2005, No 5, 723-738.10.1016/j.patcog.2004.09.004
    Search in Google Scholar
  28. 28. Li, Y.-X., C. L. Tan, X. Ding, C. Liu. Contextual Post-Processing Based on the Confusion Matrix in Offline Handwritten Chinese Script Recognition. - Pattern Recognition, Vol. 37, 2004, No 9, 1901-1912.10.1016/j.patcog.2004.03.002
    Search in Google Scholar
  29. 29. Su, T.-H., T.-W. Zhang, D.-J. Guan, H.-J. Huang. Off-Line Recognition of Realistic Chinese Handwriting Using Segmentation-Free Strategy. - Pattern Recognition, Vol. 42, 2009, No 1, 167-182.10.1016/j.patcog.2008.05.012
    Search in Google Scholar
  30. 30. Zhao, S., Z. Chi, P. Shi, H. Yan. Two-Stage Segmentation of Unconstrained Handwritten Chinese Characters. - Pattern Recognition, Vol. 36, 2003, No 1, 145-156.10.1016/S0031-3203(02)00041-9
    Search in Google Scholar
  31. 31. Itoh, N. Japanese Language Model Based on Bigrams and Its Application to On-Line Character Recognition. - Pattern Recognition, Vol. 28, 1995, No 2, 135-141.10.1016/0031-3203(94)E0053-N
    Search in Google Scholar
  32. 32. Kimura, F., T. Wakabayashi, S. Tsuruoka, Y. Miyake. Improvement of Handwritten Japanese Character Recognition Using Weighted Direction Code Histogram. -Pattern Recognition, Vol. 30, 1997, No 8, 1329-1337.10.1016/S0031-3203(96)00153-7
    Search in Google Scholar
  33. 33. Srihari, S. N., T. Hong, G. Srikantan. Machine-Printed Japanese Document Recognition. - Pattern Recognition, Vol. 30, 1997, No 8, 1301-1313.10.1016/S0031-3203(96)00168-9
    Search in Google Scholar
  34. 34. Al-Muhtaseb, H. A., S. A. Mahmo ud, R. S. Qahwaj i. Recognition of Off-Line Printed Arabic Text Using Hidden Markov Models. - Signal Processing, Vol. 88, 2008, No 12, 2902-2912.10.1016/j.sigpro.2008.06.013
    Search in Google Scholar
  35. 35. Azmi, R., E. Kabir. A New Segmentation Technique for Omnifont Farsi Text. - Pattern Recognition Letters, Vol. 22, 2001, 97-104.10.1016/S0167-8655(00)00086-6
    Search in Google Scholar
  36. 36. Dehghan, M., K. Faez, M. Ahmadi, M. Shridha r. Unconstrained Farsi Handwritten Word Recognition Using Fuzzy Vector Quantization and Hidden Markov Models. - Pattern Recognition Letters, 2001, 209-214.10.1016/S0167-8655(00)00090-8
    Search in Google Scholar
  37. 37. Mozaffari, S., K. Faez, V. Märgner, H. El-Abed. Lexicon Reduction Using Dots for Off-Line Farsi/Arabic Handwritten Word Recognition. - Pattern Recognition Letters, Vol. 29, 2008, No 6, 724-734.10.1016/j.patrec.2007.11.009
    Search in Google Scholar
  38. 38. Solimanpour, F., J. Sadri, C. Y. Suen. Standard Databases for Recognition of Handwritten Digits, Numerical Strings, Legal Amounts, Letters and Dates in Farsi Language. - In: 10th Int'l Workshop on Frontiers of Handwriting Recognition, La Baule, France, 2006.
    Search in Google Scholar
  39. 39. Ziaratban, M., K. Faez, F. Faradji. Language-Based Feature Extraction Using Template-Matching in Farsi/Arabic Handwritten Numeral Recognition. - In: 9th Int'l Conference on Document Analysis and Recognition, Curitiba, Brazil, 2007.10.1109/ICDAR.2007.4405576
    Search in Google Scholar
  40. 40. B lumen stein, M., X. Y. Liu, B. Verm a. A Modified Direction Feature for Cursive Character Recognition. - In: IEEE International Joint Conference on Neural Networks, Vol. 4, 2000, 2983-2987.
    Search in Google Scholar
  41. 41. Fitzgerald, J. A., F. Geiselbrechtinger, T. Kechadi. Application of Fuzzy Logic to Online Recognition of Handwritten Symbols. - In: Proceedings of Ninth International Workshop on Frontiers in Handwritten Recognition, 2004, 395-400.
    Search in Google Scholar
  42. 42. Fletcher, R., C. M. Reeves. Function Minimization by Conjugate Gradients. - Computer Journal, Vol. 7, 2004, 149-154.10.1093/comjnl/7.2.149
    Search in Google Scholar
  43. 43. Hagan, M. T., H. B. Demuth, M. H. Be ale. Neural Network Design. Boston, MA, PWS Publishing, 1996.
    Search in Google Scholar
  44. 44. Powell, M. J. D. Restart Procedures for the Conjugate Gradient Method. - Mathematical Programming, Vol. 12, 1977, 241-254.10.1007/BF01593790
    Search in Google Scholar
  45. 45. Beale, E. M. L. A Derivation of Conjugate Gradients. - In: F. A. Lootsma, Ed. Numerical Methods for Nonlinear Optimization. London, Academic Press, 1972.
    Search in Google Scholar
  46. 46. Mo l l e r, M. F. A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning. - Neural Networks, Vol. 6, 1993, 525-533.10.1016/S0893-6080(05)80056-5
    Search in Google Scholar
  47. 47. Battiti, R. First and Second Order Methods for Learning: Between Steepest Descent and Newton's Method. - Neural Computation, Vol. 2, 1992, No 4, 141-166.10.1162/neco.1992.4.2.141
    Search in Google Scholar
  48. 48. Sexton, A. P., V. Sorge. Database-Driven Mathematical Character Recognition, Graphics Recognition, Algorithms and Applications (GREC). - In: Lecture Notes in Computer Science (LNCS), Hong Kong, 2006, 206-217.10.1007/11767978_20
    Search in Google Scholar
  49. 49. Riedmiller, M., H. Braun. A Direct Adaptive Method for Faster Backpropagation Learning: The RPROP Algorithm. - In: Proceedings of IEEE International Conference on Neural Networks, 1993.
    Search in Google Scholar
  50. 50. De Campos, T. E., B. R. Babu, M. Varma. Character Recognition in Natural Images. - In: Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP), Lisbon, Portugal, February 2009.
    Search in Google Scholar
DOI: https://doi.org/10.2478/cait-2014-0024 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
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Language: English
Page range: 114 - 126
Published on: Jul 15, 2014
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Learning algorithm,
neural network,
Optical Character Recognition (OCR),
pattern recognition
Related subjects:
Computer sciences,
Information technology

© 2014 Marjan Kuchaki Rafsanjani, Masoud Pourshaban, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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