bibliography tkh


  1. T. K. Ho and E. T. Lee and T. T. Ho, Syntactic Approach to Image Analysis, Proc. of the ACM Computer Science Conference, pp. 395, February 1987.
  2. T. K. Ho, A Knowledge Base for Space Object Surveillance and Identification, Dept. of Computer Science Louisiana State University, Baton Rouge Louisiana, May 1987.
  3. E. T. Lee and T. Y. Young and T. K. Ho and W. Shomar, Pictorial Knowledge and Space Object Surveillance and Identification, Advances in Artificial Intelligence Research, Ed. M. B. Fishman (Ed.), Vol. 1, pp. 309--345, JAI Press, 1989.
  4. J. J. Hull and A. Commike and T. K. Ho, Multiple Algorithms for Handwritten Character Recognition, Proc. of the 1st Int l Workshop on Frontiers in Handwriting Recognition, pp. 117--124, Montreal, April 1990.
  5. T. K. Ho and J. J. Hull and S. N. Srihari, Combination of Structural Classifiers, Pre-proceeings IAPR Workshop on Syntactic and Structural Pattern Recognition, pp. 123-136, Murray Hill New Jersey, June 1990.
  6. T. K. Ho and J. J. Hull and S. N. Srihari, A Word Shape Analysis Approach to Recognition of Degraded Word Images, Proc. of the 4th USPS Advanced Technology Conference, pp. 217--231, Washington D.C., November 1990.
  7. P. Cullen and T. K. Ho and J. J. Hull and M. Prussak and S. N. Srihari, Contextual Analysis of Machine Printed Addresses, Proc. of the 4th USPS Advanced Technology Conference, pp. 779--793, November 1990.
  8. T. K. Ho and J. Favata and V. Govindaraju and S. N. Srihari, Combination of Segmentation-based and Wholistic Handwritten Word Recognition Algorithms, Proc. of the 2nd Workshop on Frontiers in Handwriting Recognition, pp. 229--240, Bonas France, September 1991.
  9. T. K. Ho and J. J. Hull and S. N. Srihari, Word Recognition with Multi-Level Contextual Knowledge, Proc. of the 1st Int l Conference on Document Analysis and Recognition, pp. 905--915, St. Malo France, October 1991.
  10. T. K. Ho, A Theory of Multiple Classifier Systems and Its Application to Visual Word Recognition, Dept. of Computer Science State University of New York at Buffalo, February 1992.
  11. T. K. Ho and J. J. Hull and S. N. Srihari, A Regression Approach to Combination of Decisions by Multiple Character Recognition Algorithms, SPIE Proc. Vol. 1661 Machine Vision Applications in Character Recognition and Industrial Inspection, San Jose CA, February 1992.
  12. P. Cullen and T. K. Ho and J. J. Hull and M. Prussak and S. N. Srihari, Contextual Analysis of Machine Printed Addresses, SPIE Proc. Vol. 1661 Machine Vision Applications in Character Recognition and Industrial Inspection, San Jose CA, February 1992.
  13. S. Khoubyari and T. K. Ho, Visual Global Context: Word Image Matching in a Methodology for Degraded Text Recognition, Proc. of the Symposium on Document Analysis and Information Retrieval, Las Vegas Nevada, March 1992.
  14. T. K. Ho and J. J. Hull and S. N. Srihari, On Multiple Classifier Systems for Pattern Recognition, Proc. of the 11th Int l Conference on Pattern Recognition, pp. 84--87, The Hague The Netherlands, September 1992.
  15. L. Li and T. K. Ho and J. J. Hull and S. N. Srihari, A Hypothesis Testing Approach to Word Recognition Using Dynamic Feature Selection, Proc. of the 11th Int l Conference on Pattern Recognition, pp. 586--589, The Hague The Netherlands, September 1992.
  16. J. J. Hull and S. Khoubyari and T. K. Ho, Word Image Matching as a Technique for Degraded Text Recognition, Proc. of the 11th Int l Conference on Pattern Recognition, pp. 665--668, The Hague The Netherlands, September 1992.
  17. P. K. Wong and T. K. Ho and S. N. Srihari, Firm Name Recognition for Automatic Address Interpretation, Proc. of the 5th USPS Advanced Technology Conference, pp. 757--770, Washington D.C., November 1992.
  18. T. K. Ho and J. J. Hull and S. N. Srihari, Combination of Decisions by Multiple Classifiers, Structured Document Image Analysis, Ed. H. S. Baird and H. Bunke and K. Yamamoto (Eds.), pp. 188--202, Springer-Verlag, Heidelberg, 1992.
  19. T. K. Ho and J. J. Hull and S. N. Srihari, A Computational Model for Recognition of Multifont Word Images, Machine Vision and Applications, Vol. 5, 3, pp. 157--168, 1992.
  20. T. K. Ho and J. J. Hull and S. N. Srihari, A Word Shape Analysis Approach to Lexicon Based Word Recognition, Pattern Recognition Letters, Vol. 13, pp. 821--826, 1992.
  21. S. N. Srihari and S. W. Lam and P. B. Cullen and T. K. Ho, Document Image Analysis and Recognition, Artificial Intelligence Methods and Applications, Ed. N. Bourbakis (ed.), pp. 590-617, World Scientific Publishing, 1992.
  22. E. M. Kleinberg and T. K. Ho, Pattern Recognition by Stochastic Modeling, Proc. of the 3rd Workshop on Frontiers in Handwriting Recognition, pp. 175--183, Buffalo New York, May 1993.
  23. T. K. Ho, Recognition of Handwritten Digits by Combining Independent Learning Vector Quantizations, Proc. of the 2nd Int l Conference on Document Analysis and Recognition, pp. 818--821, Tsukuba Science City Japan, October 1993.
  24. T. K. Ho and H. S. Baird, Perfect Metrics, Proc. of the 2nd Int l Conference on Document Analysis and Recognition, pp. 593--597, Tsukuba Science City Japan, October 1993.
  25. T. K. Ho and J. J. Hull and S. N. Srihari, Decision Combination in Multiple Classifier Systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 16, 1, pp. 66--75, January 1994.
  26. T. K. Ho and H. S. Baird, Asymptotic Accuracy of Two-Class Discrimination, Proceedings of the Third Annual Symposium on Document Analysis and Information Retrieval, pp. 275--288, Las Vegas, April 1994.
  27. T. K. Ho and H. S. Baird, Estimating the Intrinsic Difficulty of A Recognition Problem, Proceedings of the 12th Int l Conference on Pattern Recognition, pp. 178--183, Jerusalem Israel, October 1994.
  28. T. K. Ho, Selection of Image Features for Distribution-Map Classifiers, SPIE Proceedings Vol. 2422 Document Recognition II, pp. 105--114, San Jose, February 1995.
  29. T. K. Ho and H. S. Baird, Evaluation of OCR accuracy using synthetic data, Proceedings of the 4th Annual Symposium on Document Analysis and Information Retrieval, pp. 413--422, April 1995.
  30. T. K. Ho, Random Decision Forests, Proc. of the 3rd Int l Conference on Document Analysis and Recognition, pp. 278--282, Montreal Canada, August 1995.
  31. T. K. Ho and E. M. Kleinberg, Building Projectable Classifiers of Arbitrary Complexity, Proceedings of the 13th Int l Conference on Pattern Recognition, pp. 880-885, Vienna Austria, August 1996.
  32. T. K. Ho, Adaptive Coordination of Multiple Classifiers, Document Analysis Systems II, pp. 371-384, World Scientific Publishing, 1997, (Prelim. version in Proc. of the IAPR Workshop on Document Analysis Systems Malvern Pennsylvania October 1996 338-351) .
  33. S. Knerr and T. K. Ho, Commercial Exploitation of OCR and Document Analysis Systems Technology: Market and User Requirements, Document Analysis Systems II, Ed. J. J. Hull and S. Taylor, pp. 521-523, World Scientific Publishing, 1997.
  34. T. K. Ho and H. S. Baird, Large-Scale Simulation Studies in Image Pattern Recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 19, 10, pp. 1067-1079, October 1997.
  35. J. Hobby and T. K. Ho, Enhancing Degraded Document Images via Bitmap Clustering and Averaging, Proc. of the 4th Int l Conference on Document Analysis and Recognition, pp. 394--400, Ulm Germany, August 1997.
  36. T. K. Ho and H. S. Baird, Pattern Classification with Compact Distribution Maps, Computer Vision and Image Understanding, Vol. 70, 1, pp. 101-110, April 1998.
  37. T. K. Ho, The Random Subspace Method for Constructing Decision Forests, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, 8, pp. 832-844, August 1998.
  38. T. K. Ho, Nearest Neighbors in Random Subspaces, Proceedings of the 2nd Int l Workshop on Statistical Techniques in Pattern Recognition, pp. 640-648, Sydney Australia, August 1998.
  39. T. K. Ho, Bootstrapping Text Recognition from Stop Words, Proceedings of the 14th Int l Conference on Pattern Recognition, pp. 605-609, Brisbane Australia, August 1998.
  40. T. K. Ho, C4.5 Decision Forests, Proceedings of the 14th Int l Conference on Pattern Recognition, pp. 545-549, Brisbane Australia, August 1998.
  41. T. K. Ho, Fast Identification of Stop Words for Font Learning and Keyword Spotting, Proceedings of the 5th Int l Conference on Document Analysis and Recognition, pp. 333-336, Bangalore India, September 1999.
  42. T. K. Ho, Stop Word Identification for Adaptive Text Recognition, 1999, (submitted) .
  43. M. Basu and T. K. Ho, The learning behavior of single neuron classifiers on linearly separable or nonseparable input, Proceedings of the 1999 Int l Joint Conference on Neural Networks, Washington DC, July 1999.
  44. M. Basu and T. K. Ho, Review of Descent Procedures for Linear Classifiers with Linearly Separable or Nonseparable Input, 1999, (submitted) .
  45. H. Chen and T. K. Ho, Evaluation of Decision Forests on Text Categorization, Proceedings of SPIE Conference on Document Recognition and Retrieval VII, San Jose, January 2000.
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Modified: December, 1997.
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