Estimation and decision fusion: A survey

IEEE International Conference on Engineering of Intelligent Systems, ICEIS 2006

Volumn , Issue , 2006, Pages

  Sinha, Abhijit ^a   Chen, Huimin ^b   Danu, D G ^a   Kirubarajan, Thia ^a   Farooq, M ^c  

^a MCMASTER UNIVERSITY   (Canada)

^b UNIVERSITY OF NEW ORLEANS   (United States)

^c ROYAL MILITARY COLLEGE OF CANADA   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION FUSION; MATHEMATICAL TOOLS;

DECISION MAKING; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBLEM SOLVING;

DATA FUSION;

EID: 40849083858     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (38)

1. Alexandre, L., Campihlo, A. and Kamel, M., "On Combining Classifiers using Sum and Product Rules. Pattern Recognition Letters, vol. 22, pp. 1283-1289, 2001.
2. Bar-Shalom, Y. and Li, X. R., Multitarget-Multisensor Tracking: Principles and Techniques, YBS Publishing, 1995.
3. Bar-Shalom, Y. and Blair, W. D. (editors), Multitarget-Multisensor Tracking: Applications and Advances, Volume III, Artech House, 2000.
4. Bar-Shalom, Y. and Chen, H., "Multisensor Track-to-Track Association for Tracks with Dependent Errors", Proc. of IEEE CDC, Bahamas, Dec. 2004.
5. Battiti, R., and Colla, A., "Democracy in Neural Nets: Voting Schemes for Classification", Neural Networks, vol. 7, no. 4, pp. 691-707, 1994.
6. Benediktsson, J., and Swain, P., "Consensus Theoritic Classification Methods", IEEE Transactions on Systems, Man, and Cybernetics, vol. 22, no. 4, pp. 688-704, 1992.
7. Bloch, I., "Information Combination Operators for Data Fusion: A Comparative Review with Classification", IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 26, pp. 52-67, 1996.
8. Borda, J. C., "Mémoire sur les élections au scrutin", Histoire de l'Académie Royale des Sciences, Paris, 1781.
9. Breiman, L., "Stacked Regression", Machine Learning, vol. 24, no. 1, pp. 49-64, 1996.
10. Breiman, L., "Bagging Predictors", Machine Learning, vol. 26, no. 2, pp. 123-140, 1996.
11. Chen, H. and Bar-Shalom, Y., "Performance Limits of Track-to-Track Fusion versus Centralized Estimation: Theory and Application", IEEE Trans. on Aero. and Elec. Systems, Vol. 39, No. 2, pp. 386-400, April, 2003.
12. Cho, S., and Kim, J., "Combining Multiple Neural Networks by Fuzzy Integral for Robust Classification", IEEE Transactions on Systems, Man, and Cybernetics, vol. 25, no. 2, pp. 380-384, 1995.
13. Chong, C. Y., Mori, S., Barker, W. H. and Chang, K. C., "Architectures and algorithms for track association and fusion", IEEE Aerospace and Electronic Systems Magazine, Vol. 15, Issue 1, Jan. 2000.
14. Dasarathy, B., Decision Fusion. IEEE Computer Society Press, 1994.
15. Denouex, T., "A K-nearest Neighbor Classification Rule Based on Dempter-Shafer Theory", IEEE Transactions on Systems, Man, and Cybernetics, vol. 25, no. 5, pp. 804-813, 1995.
16. Drummond, O. E., "A Hybrid Sensor Fusion Algorithm Architecture and Tracklets", Porc. of SPIE Signal and Data Processing of Small Targets, Vol. 3163, 1997.
17. Drummond, O. E., "Tracklets and a Hybrid Fusion with Process Noise", Porc. of SPIE Signal and Data Processing of Small Targets, Vol. 3163, 1997.
18. Druker, H., Cortes, C., Jackel, L., LeCum, Y., and Vaprik, V., "Boosting and Other Ensemble Methods", Neural Computation, vol. 6, pp. 1289-1301, 1994.
19. Geman, S., Bienenstock, E., and Doursat, R., "Neural Networks and the Bias/Variance Dilemma. Neural Computation, vol. 4, no. 1, pp. 1-58, 1992.
20. Giacinto, G., and Roli, F., Dynamic Classifier Selection Based on Multiple Classifier Behaviour. Pattern Recognition, vol. 34, pp. 1879-1881, 2001.
21. Grabisch, M., "Classification by Fuzzy Integral: Performance and Tests", Fuzzy Sets and Systems, vol. 65, pp. 255-271, 1994.
22. Gunatilaka, A. H., and Baertlein, B. A, "Feature-Level and Decision-Level Fusion of Noncoincidently Sampled Sensors for Land Mine De tection", IEEE Trans, on Pattern Analysis and Machine Intelligence, Vol. 23, Issue 6, pp. 577-589, June 2001.
23. Hall, D. L., and McMullen, S. A. H., Mathematical Techniques in Multisensor Data Fusion, Second Edition, Artech House, 2004.
24. Hansen, L. and Salamon, P., "Neural Networks Ensembles", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 10, pp. 993-1001, 1990.
25. Ho, T., Hull, J., and Srihari, S., "Decision Combination in Multiple Classifier Systems", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no. 1, pp. 66-75, 1994.
26. Jazwinski, A. H., Stochastic Processes and Filtering Theory, Academic Press, 1970.
27. Jordon, M., and Jacobs, R., "Hierarchical Mixtures of Expert and the EM Algorithm. Neural Computing, pp. 181-214, 1994.
28. Julier, S. and Uhlmann, J. K., "A Non-Divergent Estimation Algorithm in the Presence of Unknown Correlations", American Control Conference, Vol. 4, pp. 2369-2373, Albuquerque, NM USA, June 1997.
29. Julier, S. and Uhlmann, J. K., "General Decentralized Data Fusion with Covariance Intersection", Ch. 12 in D. L. Hall and J. Llinas (editors) Handbook ofMultisensor Data Fusion,CRC Press, 2001.
30. Kam, M., Zhu, X., and Kalata, P., "Sensor Fusion for Mobile Robot Navigation", Proceeding of the IEEE, Vol. 85, No. 1, Jan. 1997.
31. Kittler, J., Hatef, M., Duin, R., and Matas, J., "On Combining Classifiers", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 20, no. 3, pp. 226-239, 1998.
32. Kuncheva, L., "Switching Between Selection and Fusion in Combining Classifiers: An Experiment" IEEE Transactions on Systems, Man, and Cybernetics - Part B, vol. 32, no. 2, pp. 146-156, 2002.
33. Li, X. R., "Optimal linear estimation fusion-part VII: dynamic systems" Proc. of the Sixth International Conference of Information Fusion, pp. 455-462, 2003.
34. Murphy, R. R., "Dempster-Shafer Theory for Sensor Fusion in Autonomous Mobile Robots", IEEE Trans. on Robotics and Automation, Vol. 14, No. 2, pp. 197-206, April 1998.
35. Schapire, R., "The Strength of Weak Learnability", Machine Learning, vol. 5, pp. 197-227, 1990.
36. Tumer, K., and Ghosh, J., "Order Statistics Combiners for Neural Classifiers", In World Congress on Neural Networks, pp. 1:31-34, Washington, DC, 1995.
37. Ueda, N., "Optimal Linear Combination of Neural Networks for Improving Classification Performance", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 2, pp. 207215, 2000.
38. Wolpert, D., "Stacked Generalization", Neural Networks, vol. 5, pp. 241-259, 1992.