Region-growing techniques based on texture for provincing the ocean floor

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Region-growing techniques based on texture for provincing the ocean floor

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ACM Southeast Regional Conference archive
Proceedings of the 36th annual Southeast regional conference table of contents

Pages: 99 - 103

Year of Publication: 1998

ISBN:1-58113-030-9

Authors

Bruce A. Wooley	Box 9637, Mississippi State, MS
George B. Smith	Box 9637, Mississippi State, MS

Sponsor

ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Peter Cheeseman , John Stutz, Bayesian classification (AutoClass): theory and results, Advances in knowledge discovery and data mining, American Association for Artificial Intelligence, Menlo Park, CA, 1996
	2	Usama M. Fayyad , Gregory Piatetsky-Shapiro , Padhraic Smyth, From data mining to knowledge discovery: an overview, Advances in knowledge discovery and data mining, American Association for Artificial Intelligence, Menlo Park, CA, 1996
	3	Hodges, Julia, Susan Bridges, Bruce Wooley, Donald Karpovich, and George B. Smith. 1997. Knowledge discovery in an object-oriented oceanographic database system, http://www.c s.msstate.edu/PUBLICATIONS/technicalReports.html
	4	Reed, Thomas Beckett IV, and Donald Hussong. 1989. Digital image processing techniques for enhancement and classification of SeaMARC II side scan sonar imagery. Journal of Geophysical Research 94(B6): 7469-90.
	5	Xu, Jian-hua. 1992. Texture analysis approaches to extract ocean wavelengths, directions, and heights from ocean wave images. Optical Engineering. 31(8) 1705- 14.