Publications

2004

  • C. Kamath, “Statistics and Practical Applications of Data Mining: Highlights from SDM04,” SIAM News, Volume 37, Number 6, July/August 2004.
  • A. Lazarevic, Kanapady, R. and Kamath, C., “Effective Localized Regression for Damage Detection in Large Complex Mechanical Structures,” Proceedings, ACM International Conference on Knowledge Discovery and Data Mining, pp 450-459, August 22-25, 2004, Seattle, WA.
  • Cantu-Paz, E., Newsam, S., Kamath, C., “Feature Selection in Scientific Applications,” Proceedings, ACM International Conference on Knowledge Discovery and Data Mining, pp 788-793, August 22-25, 2004, Seattle, WA.
  • Newsam, S. and C. Kamath, “Retrieval using texture features in high resolution multi-spectral satellite imagery,” Data Mining and Knowledge Discovery: Theory, Tools, and Technology, VI, SPIE Volume 5433, pp. 21-32, SPIE Defense and Security, Orlando, April 2004.
  • Cantu-Paz, E., Cheung, S-C., and Kamath, C., “Retrieval of Similar Objects in Simulation Data Using Machine Learning Techniques,” Image Processing: Algorithms and Systems III, SPIE Volume 5298, pp 251-258. SPIE Electronic Imaging, San Jose, January 2004.
  • Cheung, S.-C., and C. Kamath, “Robust techniques for background subtraction in urban traffic video,” Video Communications and Image Processing, Volume 5308, pp 881-892, SPIE Electronic Imaging, San Jose, January 2004.
  • Weeratunga S. and C. Kamath, “An investigation of implicit active contours for scientific image segmentation,” Video Communications and Image Processing, SPIE Volume 5308, pp. 210-221, SPIE Electronic Imaging, San Jose, January 2004.

2003

  • Lazarevic, A., R. Kanapady, C. Kamath, V. Kumar, and K. Tamma, “Localized Prediction of Continuous Target Variables Using Hierarchical Clustering,” Proceedings, IEEE International Conference on Data Mining, pp. 139-146, Melbourne, Florida, Nov. 2003.
  • Moelich, M., “Autonomous Motion Segmentation of Multiple Objects in Low Resolution Video Using Variational Level Sets,” LLNL Technical report, UCRL-TR-201054., November 19, 2003.
  • Gyaourova, A., C. Kamath, and S.-C. Cheung, “Block matching for object tracking,” LLNL Technical report, October 2003. UCRL-TR-200271.
  • Lazarevic, A., Kanapady, R., Kamath, C., Tamma K., Kumar, V., “Damage Detection Employing Novel Data Mining Techniques,” book chapter, New Generation of Data Mining Applications, IEEE Press, August 2003.
  • Kamath, C., E. Cantu-Paz, S.-C. Cheung, I. K. Fodor, and N. Tang, “Experiences in mining data from computer simulations,” book chapter, New Generation of Data Mining Applications, IEEE Press, August 2003.
  • Cheung S.-C. and C. Kamath, “Initial experiences with retrieving similar objects in simulation data,” Proceedings, Sixth Workshop on Mining Scientific and Engineering Datasets, in conjunction with the Third SIAM conference on Data Mining, May 3, 2003, pp 11-18.
  • Fodor, I.K. and C. Kamath, “Using independent component analysis to separate signals in climate data,” Proceedings, Independent component analysis, Wavelets, and Neural Networks, SPIE Aerosense, Orlando, April 2003.
  • I. K. Fodor and Kamath, C., “Efficient segmentation of spatio-temporal data from simulations,” Proceedings, Image and Video Communications and Processing, SPIE Electronic Imaging, San Jose, January 2003.
  • Sengupta, S. K., C. Kamath, D. Poland, J. Futterman, “Detecting human settlements in Satellite Images,” Proceedings, Optical Engineering at the Lawrence Livermore National Laboratory, SPIE Photonics West, Lasers and Applications in Science and Engineering, San Jose, January 2003.
  • Kamath, C., S. Sengupta, D. Poland, and J. Futterman, “On the use of machine vision techniques to detect human settlements in satellite images, Proceedings, Image Processing: Algorithms and Systems II, SPIE Electronic Imaging, San Jose, January 2003.
  • Weeratunga S.K., and C. Kamath, “A comparison of PDE-based non-linear anisotropic diffusion techniques for image denoising,” Proceedings, Image Processing: Algorithms and Systems II, SPIE Electronic Imaging, San Jose, January 2003.

2002

  • Gyaourova, A., C. Kamath, and I. K. Fodor, “Undecimated Wavelet Transforms for Image De-Noising,” LLNL Technical report, UCRL-ID-150931.
  • Kirshner, S., I. V. Cadez, P. Smyth, C. Kamath, and E. Cantu-Paz, “Probabilistic Model-based Detection of Bent-double radio galaxies,” poster presentation at International Conference on Pattern Recognition, August 2002.
  • Kamath, C., E. Cantu-Paz, I.K. Fodor, N. Tang, “Classification of bent-double galaxies in the FIRST survey,” IEEE Computing in Science and Engineering, July/August 2002, pp 52-60,.
  • Kamath, C., “Mining the Sky: Data Analysis Meets Astronomy,” SIAM News, April 2002.
  • Cantu-Paz, E., and C. Kamath, “Evolving neural networks for the classification of galaxies,” Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2002, pp. 1019-1026, Morgan Kaufmann Publishers, San Francisco, 2002, UCRL-JC-147020. Tied for the best paper award in the Real World Applications Category.
  • Fodor, I. K., and C. Kamath, “On the use of independent component analysis to separate meaningful sources in global temperature series,” Joint Statistical Meetings, August 2002.
  • Kamath, C., “Mining Science and Engineering Data: An Overview,” book chapter, Handbook of Data Mining, Nong Ye (ed.), pp 549-572, Lawrence Erlbaum Associates. New Jersey, 2003.
  • Kamath, C., and E. Cantu-Paz, “Classification of bent-double galaxies: Experiences with ensembles of decision trees,” Proceedings, Fifth Workshop on Mining Scientific Datasets, pp. 43-50, Held in conjunction with the Second SIAM International Conference on Data Mining, April 13, 2002.
  • Cantu-Paz E., and C. Kamath, “Evolving neural networks to identify Bent-Double Galaxies in the FIRST Survey,” Neural Networks, Volume 16, No. 3-4, pp. 507-517, 2003.
  • Kamath, C., “Workshop report: The Fourth Workshop on Mining Scientific Datasets,” SigKDD Newsletter, Volume 3, Issue 2, pp. 68-69, January 2002.
  • Weeratunga S.K. and C. Kamath, “PDE-based non-linear diffusion techniques for denoising scientific/industrial images: An empirical study,” Proceedings, Image Processing: Algorithms and Systems, SPIE Electronic Imaging, pp. 279-290, San Jose, January 2002.
  • Kamath, C., E., Cantú-Paz, and D. Littau, “Approximate Splitting for Ensembles of Trees using Histograms,” Proceedings, Second SIAM International Conference on Data Mining, pp. 370-383, April 2002.