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Nonparametric analysis of Minnesota spruce and aspen tree data and LANDSAT dataThe application of nonparametric methods in data-intensive problems faced by NASA is described. The theoretical development of efficient multivariate density estimators and the novel use of color graphics workstations are reviewed. The use of nonparametric density estimates for data representation and for Bayesian classification are described and illustrated. Progress in building a data analysis system in a workstation environment is reviewed and preliminary runs presented.
Document ID
19850007944
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Authors
Scott, D. W.
(Rice Univ. Houston, TX, United States)
Jee, R.
(Rice Univ. Houston, TX, United States)
Date Acquired
August 12, 2013
Publication Date
January 1, 1984
Publication Information
Publication: Texas A and M Univ. Proc. of the 2nd Ann. Symp. on Math. Pattern Recognition and Image Analysis Program
Subject Category
Earth Resources And Remote Sensing
Accession Number
85N16253
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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