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Robust support vector machine with bullet hole image classification
Abstract
This paper proposes a robust support vector machine for pattern classification, which aims at solving the over-fitting problem when outliers exist in the training data set. During the robust training phase, the distance between each data point and the center of class is used to calculate the adaptive margin. The incorporation of the average techniques to the standard support vector machine (SVM) training makes the decision function less detoured by outliers, and controls the amount of regularization automatically. Experiments for the bullet hole classification problem show that the number of the support vectors is reduced, and the generalization performance is improved significantly compared to that of the standard SVM training.
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Citations
Cited by
Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys · doi:10.1145/1541880.1541882 · Cited by 11,687
Pimentel, M. A. F., Clifton, D. A., Clifton, L., & Tarassenko, L. (2014) · Signal Processing · doi:10.1016/j.sigpro.2013.12.026 · Cited by 1,649
Support Vector Machine Classifier With Pinball Loss
Huang, X., Shi, L., & Suykens, J. A. K. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.178 · Cited by 355
Metadata
- Authors
- Song, Q., Hu, W., & Xie, W.
- Venue
- IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews)
- Published
- 2002-11
- Volume
- 32
- Issue
- 4
- Pages
- 440-448
- ISSN
- 1094-6977 (ISSN-L)
- OpenAlex
- W2141718589
- Cited by
- 208
- References
- 0
- FWCI
- 4.35
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Robust support vector machine with bullet hole image classification. https://app.cochat.ai/papers/10.1109/tsmcc.2002.807277
- The paper
- Song, Q., Hu, W., & Xie, W. (2002). Robust support vector machine with bullet hole image classification. IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews). https://doi.org/10.1109/tsmcc.2002.807277
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
