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Using the RRT algorithm to optimize classification systems for handwritten digits and letters

Published: 16 March 2008 Publication History

Abstract

Multi-objective genetic algorithms have been often used to optimize classification systems, but little is discussed on their computational cost to solve such problems. This paper optimizes a classification system with an annealing based approach, the Record-to-Record Travel algorithm. Results obtained are compared to those obtained with a multi-objective genetic algorithm in the same approach. Experiments are performed with isolated handwritten digits and uppercase letters, demonstrating both the effectiveness and lower computational cost of the annealing based approach.

References

[1]
V. di Lecce, G. Dimauro, S. Impedovo, G. Pirlo, and A. Salzo. Zoning Design for Hand-Written Numeral Recognition. In Proceedings of the Seventh international Workshop on Frontiers in Handwriting Recognition -- IWFHR-7, pages 583--588, Amsterdan, 2000. Nijmegenl: International Unipen Foundation.
[2]
J. Handi and J. Knowles. Feature subset selection in unsupervised learning via multiobjective optimization. International Journal on Computational Intelligence Research, 3(1):217--238, 2006.
[3]
F. Kimura, S. Inoue, T. Wakabayashi, S. Tsuruoka, and Y. Miyake. Handwritten Numeral Recognition using Autoassociative Neural Networks. In Proceedings of the International Conference on Pattern Recognition, pages 152--155, 1998.
[4]
J. Kittler, M. Hatef, R. P. W. Duin, and J. Matas. On combining classifiers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(3):226--239, 1998.
[5]
L. I. Kuncheva and L. C. Jain. Design classifier fusion systems by genetic algorithms. IEEE Transactions on Evolutionary Computation, 4(4):327--336, 2000.
[6]
Z.-C. Li and C. Y. Suen. The partition-combination method for recognition of handwritten characters. Pattern Recognition Letters, 21(8):701--720, 2000.
[7]
L. S. Oliveira, R. Sabourin, F. Bortolozzi, and C. Y. Suen. Automatic Recognition of Handwritten Numerical Strings: A Recognition and Verification Strategy. IEEE Trans. on Pattern Alalysis and Machine Intelligence, 24(11):1438--1454, 2002.
[8]
J. W. Pepper, B. L. Golden, and E. A. Wasil. Solving the traveling salesman problem with annealing-based heuristics: A computational study. IEEE Trans. on Systems, Mand and Cybernetics -- Part A: Systems and Humans, 32(1):72--77, 2002.
[9]
P. V. W. Radtke, T. Wong, and R. Sabourin. Classification system optimization with multi-objective genetic algorithms. In Proceedings of the 10th International Workshop on Frontiers in Handwriten Recognition (IWFHR 2006), pages 331--336. IAPR, 2006.
[10]
P. V. W. Radtke, T. Wong, and R. Sabourin. An evaluation of over-fit control strategies for multi-objective evolutionary optimization. In Proceedings of the International Joint Conference on Neural Networks (IJCNN 2006), pages 6359--6366. IEEE Computer Society, 2006.
[11]
D. Ruta and B. Gabrys. Classifier Selection for Majority Voting. Information fusion, 6:63--81, 2005.
[12]
G. Tremblay, R. Sabourin, and P. Maupin. Optimizing nearest neighbour in random subspaces using a multi-objective genetic algorithn. In 17th International Conference on Pattern Recognition -- ICPR2004, pages 208--211, Cambridge, U.K., August 2004. IEEE Computer Society.
[13]
A. Tsymbal, M. Pechenizkiy, and P. Cunningham. Sequential genetic search for ensemble feature selection. In Proceddings of International Joint Conference on Artificial Intelligence, pages 877--882, 2005.

Cited By

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  • (2022)A unified feature descriptor for generic character recognition based on zoning and histogram of gradientsNeural Computing and Applications10.1007/s00521-022-07110-x34:14(12223-12234)Online publication date: 14-Mar-2022
  • (2020)Pattern Recognition of Handwritten English CharactersMatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition10.4018/978-1-7998-1554-9.ch005(128-144)Online publication date: 2020
  • (2019)A Survey of Handwritten Character Recognition with MNIST and EMNISTApplied Sciences10.3390/app91531699:15(3169)Online publication date: 4-Aug-2019
  • Show More Cited By

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cover image ACM Conferences
SAC '08: Proceedings of the 2008 ACM symposium on Applied computing
March 2008
2586 pages
ISBN:9781595937537
DOI:10.1145/1363686
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 16 March 2008

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Author Tags

  1. RRT algorithm
  2. classification systems
  3. ensemble of classifiers
  4. local search

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SAC '08
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SAC '08: The 2008 ACM Symposium on Applied Computing
March 16 - 20, 2008
Fortaleza, Ceara, Brazil

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

View all
  • (2022)A unified feature descriptor for generic character recognition based on zoning and histogram of gradientsNeural Computing and Applications10.1007/s00521-022-07110-x34:14(12223-12234)Online publication date: 14-Mar-2022
  • (2020)Pattern Recognition of Handwritten English CharactersMatConvNet Deep Learning and iOS Mobile App Design for Pattern Recognition10.4018/978-1-7998-1554-9.ch005(128-144)Online publication date: 2020
  • (2019)A Survey of Handwritten Character Recognition with MNIST and EMNISTApplied Sciences10.3390/app91531699:15(3169)Online publication date: 4-Aug-2019
  • (2011)Convolutional Neural Network Committees for Handwritten Character ClassificationProceedings of the 2011 International Conference on Document Analysis and Recognition10.1109/ICDAR.2011.229(1135-1139)Online publication date: 18-Sep-2011

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