Quantitative analysis of spatio-temporal decision fusion based on the majority voting technique

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5434, Issue , 2004, Pages 13-24

  Wu, Hongwei ^a   Mendel, Jerry M ^a  

^a University of Southern California ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION FUSION; DECISION MATRIX; MAJORITY VOTING TECHNIQUE; SMOKE DENSITY;

ALGORITHMS; PARALLEL PROCESSING SYSTEMS; PATTERN RECOGNITION; PROBABILITY DISTRIBUTIONS; PROBLEM SOLVING; REGRESSION ANALYSIS; SIGNAL PROCESSING; SPACE TIME ADAPTIVE PROCESSING; THEOREM PROVING;

DECISION THEORY;

EID: 3843089551     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.541715     Document Type: Conference Paper

References (34)

1. M. A. Abidi and R. C. Gonzalez, Data Fusion in Robotics and Machine Intelligence, Academic, Boston, MA, 1992.
2. Proc. The Fifth International Conference on Information Fusion, Annapolis, MD, July 2002.
3. D. L. Hall, R. J. Linn, and J. Llinas, "A survey of data fusion systems," Proc. SPIE Conf. on Data Structure and Target Classifications 1470, pp. 13-36, (Orlando, FL), April 1991.
4. D. L. Hall and J. Llinas, "An introduction to multisensor data fusion," Proceedings of the IEEE 85, pp. 6-23, January 1997.
5. L. A. Klein, Sensor and Data Fusion Concepts and Applications, 2nd Edition, SPIE-The International Society for Optical Engineering, Bellingham, Washington, 1999.
6. J. Kittler, M. Hatef, R. P. W. Duin, and J. Matas, "On combining classifiers," IEEE Transactions on Pattern Recognition and Machine Intelligence 20(3), 1998.
7. C. D and X. Cheng, "Majority vote based on weak classifiers," WCCC-ICSP 2000 3, pp. 1560-1562, 2000.
8. L. K. Hansen and P. Salamon, "Neural network ensembles," IEEE Trans. Pattern Analysis and Machine Intelligence 12, pp. 993-1001, October 1990.
9. J. Kittler and F. M. Alkoot, "Sum versus vote fusion in multiple classifier systems," IEEE Transactions on Pattern Analysis and Machine Intelligence 25(1), pp. 110-115, 2003.
10. L. Lam and C. Y. Suen, "Application of majority voting to pattern recognition: an analysis of its behavior and performance," IEEE Trans. on Systems, Man and Cybernetics-Part A: System and Humans 27, pp. 553-568, September 1997.
11. P. S. Parmpero and A. C. P. L. F. de Carvalho, "Recognition of vehicles silhouette using combination of classifiers," Proc. of the 1998 IEEE International Conference and IEEE World Congress on Computational Intelligence 3, pp. 1723-1726, 1998.
12. M. van Erp, L. Vuurpijl, and L. Schomaker, "An overview and comparison of voting methods for pattern recognition," Proc. of the Eighth International Workshop on Frontiers in Handwriting Recognition, pp. 195-200, 2002.
13. S. Wesolkowski and K. Hassanein, "A comparative study of combination schemes for an ensemble of digit recognition neural networks," Proc. of the 1997 IEEE International Conference on Computational Cybernetics and Simulation 4, pp. 3534-3539, 1997.
14. T. K. Ho, J. J. Hull, and S. N. Srihari, "Decision combination in multiple classifier systems," IEEE Trans. Pattern Analysis and Machine Intelligence 16, pp. 66-75, January 1994.
15. J. R. Parker, "Combining multiple non-homogeneous classifiers: an empirical approach," Proc. of the first IEEE International Conference on Cognitive Informatics, pp. 288-292, 2002.
16. L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their applications to handwriting recognition," IEEE Trans. Systems, Man and Cybernetics 22(3), pp. 418-435, 1992.
17. F. M. Alkoot and J. Kittler, "Improving the performance of the product fusion strategy," Proc. of the 15th International Conference on Pattern Recognition 2, pp. 164-167, 2000.
18. S. B. Cho and J. H. Kim, "Combining multiple neural networks by fuzzy integral for robust classification," IEEE Trans. Systems, Man, and Cybernetics 25(2), pp. 153-160, 1995.
19. E. Clavier, E. Trupin, M. Laurent, S. Diana, and J. Labiche, "Classifiers combination for forms sorting," Proc. of the 15th International Conference on Pattern Recognition 1, pp. 932-935, 2000.
20. J. Franke and E. Mandler, "A comparison of two approaches for combining the votes of cooperating classifiers," Proc. 11th IAPR Int'l Conf. Pattern Recognition, Conf. B: Pattern Recognition Methdology and Systems 2, pp. 611-614, 1992.
21. Hashem and B. Schmeiser, "Improving model accuracy using optimal linear combinations of trained neural networks," IEEE Trans. Neural Networks 6(3), pp. 792-794, 1995.
22. A. Hojjatoleslami and J. Kittler, "Strategies for weighted combination of classifiers employing shared and distinct representations," Proc. of the Fourteenth International Conference on Pattern Recognition 1, pp. 338-340, 1998.
23. K. Kirchhoff and J. A. Bilmes, "Dynamic classifier combination in hybrid speech recognition systems using utterance-level confidence values," Proc. of ICASSP'99 2, pp. 693-696, 1999.
24. X. Lin, X. Ding, and Y. Wu, "Handwritten numeral recognition using mfnn based multiexpert combination strategy," Proc. of the Fourth International Conference on Document Analysis and Recognition 2, pp. 471-474, 1997.
25. T. D. Pham, "Combination of multiple classifiers using adaptive fuzzy integral," Proc. of ICAIS 2002, pp. 50-55, 2002.
26. S. Procter and J. Illingworth, "Combining hmm classifiers in a handwritten text recognition system," Proc. of ICIP 98 2, pp. 934-938, 1998.
27. G. Rogova, "Combining the results of several neural network classifiers," Neural Networks 7(5), pp. 777-781, 1994.
28. H. Xue and V. Govindaraju, ""performance prediction for handwritten word recognizers and its application to classifier combination," Proc. of the 16th International Conference on Pattern Recognition 3, pp. 241-244, 2002.
29. C. Dietrich, F. Schwenker, and G. Palm, "Decision templates for the classification of bioacoustic time series," Proc. of IEEE Workshop on Neural Networks and Signal Processing, pp. 159-168, 2002.
30. F. Schwenker, C. Dietrich, H. A. Kestler, K. Riede, and G. Palm, "Radial basis function neural networks and temporal fusion for the classification of bioacoustic time series," Neurocomputing 51, pp. 265-275, 2003.
31. D.-S. Lee and S. N. Srihari, "Handprinted digit recognition: a comparison of algorithms," Proc. 3rd Int. Workshop Frontiers Handwriting Recognition, pp. 153-162, (Buffalo, NY), May 1993.
32. G. Casella and R. L. Berger, Statistical Inference, Second Edition, Duxbury Press, Pacific Grove, CA, 2002.
33. N. C. de Condorcet, Essai sur l'application de l'analyse à la probabilité des décisions redues à la pluralité des voix, Paris, France, 1785.
34. H. Wu and J. M. Mendel, "Useful bounds for majority voting decision fusion." submitted to Journal of Information Fusion for review, 2004.