name: Byoung-Doo Kang

 

Postdoctoral,  ViGIR Lab

 

E-mail: kangby@mizzou.edu


Education

-  Ph.D. Computer Science, Inje University, KOREA, 2007.

Dissertation title: "A Robust Face Tracking System"

-  M.S. Computer Science, Inje University, KOREA, 2003.

Thesis title: "An Intrusion Detection System Using Time Delay Neural Networks"

-  B.S. Computer Science, Inje University, KOREA, 2001.

 

Employment

- 2003~2007, a lecturer, School of Computer Engineering, Inje University, KOREA.

 

Research Interests

- Pattern Recognition, Image Processing, Machine Learning, Computer Vision

 

Demo

    - A Robust Face Tracking System

 

Teaching

- Image Processing Programs

- Signal Processing

- Neural Networks

- Support Vector Machine

- Programming Languages (with Visual C++, Java)

 

Professional Societies

- Member of KMS(Korea Multimedia Society)

 

Papers

International Journals

- Byoung-Doo Kang, et al., “Computer-aided Analysis and Classification of Breast Tissue Images,” The Journal on Information Technology in Healthcare, Vol. 2 pp 345~349, 2006.

 

Domestic Journals

- Byoung-Doo Kang, et al., “A Robust Face Tracking System using Effective Detector and Kalman Filter,” The Journal of Korea Multimedia Society, Vol. 10, pp. 26~35, 2007.

- Byoung-Doo Kang, et al., “Face Detection using Region Segmentation on Complex Image,” The Journal of Korea Multimedia Society, Vol. 2, pp. 160~171, 2006.

- Byoung-Doo Kang, et al., “Effective Face Detection using Principle Component Analysis and Support Vector Machine,” The Journal of Korea Multimedia Society, Vol. 11, pp. 1435~1444, 2006. 9.

- Byoung-Doo Kang, et al., “An Intrusion Detection System using Time Delay Neural Networks,” The Journal of Korea Multimedia Society, Vol.5, pp. 778~787, 2003, 6.

 

International Conferences

- Byoung-Doo Kang, et al., “Effective Detector and Kalman Filter Based Robust Face Tracking System,” LNCS 4319, Advances in Image and Video Technology, PSIVT'06, pp. 453~462, 2006.

- Byoung-Doo Kang, et al., “Hierarchical Classification of Object Images Using Neural Networks,” LNCS 3972, International Symposium on Neural Networks, pp. 322~330, 2006.

- Byoung-Doo Kang, et al., “A Mutated Intrusion Detection System using Principal Component Analysis and Time Delay Neural Network,” LNCS 3973, International Symposium on Neural Networks, pp. 246~245, 2006.

- Byoung-Doo Kang, et al., “Effective Face Detection using a Small Quantity of Training Data,” LNCS 4319, Advances in Image and Video Technology, PSIVT'06, pp. 553~562, 2006.

- Byoung-Doo Kang, et al., “Classification of Breast Tissue Images based on Wavelet Transform using Discriminant Analysis, Neural Network and SVM,” In Proceedings of the 7th International Workshop on Enterprise Networking and Computing in Healthcare Industry, pp. 345~349, 2005.

- Byoung-Doo Kang, et al., “An Intrusion Detection System using Principle Component Analysis and Time Delay Neural Network,” In Proceedings of the 7th International Workshop on Enterprise Networking and Computing in Healthcare Industry, pp. 442~445, 2005.

 

Domestic Conferences

- Byoung-Doo Kang, et al., "Hierarchical Classification of Object Images Using Neural Networks," Proceedings of Korea Information Science, Vol. 1, No. 2, pp. 6-8, 2005.10.

- Byoung-Doo Kang, et al., "Intrusion Detection System using Principle Component Analysis and Support Vector Machine," Proceedings of Korea Multimedia Society, Vol. 6, No. 1, pp. 314-317, 2003.5.

- Byoung-Doo Kang, et al., "PCA and TDNN-based Abnormal Packet Detection," Proceedings of Korea Information Processing Society, Vol. 10, No. 1, pp. 285-288, 2003.5.

- Byoung-Doo Kang, et al., "Intrusion Detection System using Time Delay Neural Network," Proceedings of Korea Multimedia Society, Vol. 4, No. 2, pp. 662-665, 2001.11.

 

Books

- Byoung-Doo Kang, et al.(Korean Book), Guide to Computer Utilities, Ehan Press, 2005.02.

 

Research Project

- Byoung-Doo Kang, Development of Music Genre Classification System Using TDNN, Korea Science and Engineering Foundation, 2001.

 

- Byoung-Doo Kang, Development of Human Tracking Robot System Using multi-vision, Korea Science and Engineering Foundation, NURI(New University for Regional Innovation), 2007.