Comparison of approaches to classifier fusion for improving mine detection/classification performance

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 4742, Issue I, 2002, Pages 431-439

  Bello, Martin G ^a  

^a BAE SYSTEMS   (United Kingdom)

Author keywords

Automatic classification; Bagging; Boosting; Detection; Mine hunting; Neural network training

Indexed keywords

ALGORITHMS; IMAGE PROCESSING; NEURAL NETWORKS; SONAR;

SIDE-SCAN SONAR IMAGERY;

EXPLOSIVES;

EID: 0036438345     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.479115     Document Type: Conference Paper

References (9)

1. C. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, New York, 1995.
2. Kohavi, R. and Bauer, E., "An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants", Machine Learning, Vol. 36, 1999, pp. 105-142.
3. D.H. Kill et. al., "Reducing Model- and Data-Mismatch Errors in Image Compression by Combining Region Dependent Transform-Coefficient Encoding with Normalization and Content-Adaptive Coding", (submitted for publication to the IEEE Journal of Ocean Engineering).
4. M.G. Bello, "A Markov Random Field Based Anomaly Screening Algorithm," Proceeding of SPIE '95, Vol. 2496, April 1995.
5. R. Haralick and L. Shapiro, Computer and Robot Vision Volume-I, Addison Wesley Publishing Co., Reading, Mass., 1992.
6. K.R. Rao and P. Yip, Discrete Cosine Transform: Algorithms, Advantages, Applications, Academic Press, New York, 1990.
7. B. Efron and R. Tibshirani, An Introduction to the Boostrap, Chapman and Hall/CRC, New York, 1993.
8. M.G. Bello, Comparison of Two Classifier Training Methodologies for Underwater Mine-Detection/Classification, Proceedings of SPIE 2001, Vol. 4394, April 2001.
9. M.G. Bello, "Comparison of Parametric and Nonparametric ROC Confidence Bound Construction in the Context of Acoustic/Magnetic Fusion Systems for Mine-hunting", Proceedings of SPIE '98, April 1998.