References
- R. Plamondon and G. Lorette, "Automatic Signature Verification and Writer Identification The State of The Art", Patten Recognition, vol. 22, no. 2, pp. 107-131, 1989. https://doi.org/10.1016/0031-3203(89)90059-9
- S. H. Kim, "A Technique of Calculating a Weighted Euclidean Distance with a Personalized Feature Set in Parametric Signature Verification", Journal of Korea Society for Simulation, vol. 14, no. 3, pp. 137-146, September 2005.
- D. H. Yang, D. J. Lee and M. G. Chun, "On-line Signature Verification Using Fusion Model Based on Segment Matching and HMM", Journal of Fuzzy Logic and Intelligent Systems, vol. 15, no. 1, pp.12-17, 2005. https://doi.org/10.5391/JKIIS.2005.15.1.012
- J. Kim, J. R. Yu and S. H. Kim, "Learning of Prototypes and Decision Boundaries for a Verification Problem have only Positive Samples,"Pattern Recognition Letters, Vol.17, pp.691-697, 1996. https://doi.org/10.1016/0167-8655(96)00016-5
- J. O. Min, D. J. Lee and M. G. Chun, "Multi-modal Biometrics System Based on Face and Signature by SVM Decision Rule", The KIPS transactions, vol. 11B, no. 7, pp. 885-892, Dec 2004. https://doi.org/10.3745/KIPSTB.2004.11B.7.885
- Vladimir Vapnik, Statistical Learning Theory, John Wiley & Sons, New York, 1998.
- Ashis Pradhan, "Support Vector Machine-A Survey," International Journal of Emerging Technology and Advanced Engineering, Vol. 2, No. 8, pp. 82-85, Aug. 2012.
- J. Park and T. Hong, "The Prediction of DEA based Efficiency Rating for Venture Business Using Multi-class SVM", Asia Pacific Journal lf Information System, vol. 19, no. 2, pp. 439-155, June 2009.
- M. K. Choi, H. G. Lee and S. C. Lee, "A new classification model of weighted SVM based on effectiveness", Korean Institute of Next Generation Computing, vol. 9, no. 1, pp. 63-73, February 2013.
- S. Y. Choi and H. C. Ahn, "Optimized Bankruptcy Prediction through Combing SVM with Fuzzy Theory", Journal of Digital Convergence, vol. 13, no. 3, pp. 155-165, Mar 2015. https://doi.org/10.14400/JDC.2015.13.3.155
- Z. G. Yan, Y. X. Yang and Y. J. Ding, "An Experimental Study of the Hyper-parameters Distribution Region and Its Optimization Method for Support Vector Machine with Gaussian Kernel", International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 6, no. 5, pp.437-446, 2013. https://doi.org/10.14257/ijsip.2013.6.5.38
- J. W. Lee D. H. Lee and I. S. Kim, "Method of Detecting Smishing using SVM", Journal of Security Engineering, vol. 10, no. 6, pp. 655-668, Dec 2013. https://doi.org/10.14257/jse.2013.12.01
- B. S. Kang, H. S. Jung, H. S. Lee, Y. H. Im, Y. W. Chung and D. H. Park, "Real Time Watch List Identification System using a Hybrid Hierarchical SVM", Journal of Security Engineering, vol. 7, no. 5, pp. 479-493, October 2010.
- Y. S. Hwang, J. C. Moon and S. J. Cho, "Classification of Malicious Web Pages by Using SVM", Journal of The Korean Society of Computer and Information, vol. 17, no. 3, pp. 77-83, March 2012.
- G. Y. Heo and S. H. Kim, "Context-Aware Fusion with Support Vector Machine", Journal of The Korean Society of Computer and Information, vol. 19, no. 6, pp. 19-26, June 2014.