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  • 1
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    Multivariate spline methods in surface fitting (1984)
    In:  Other Sources
    Details
    Publication Date: 2016-03-09
    Description: The use of spline functions in the development of classification algorithms is examined. In particular, a method is formulated for producing spline approximations to bivariate density functions where the density function is decribed by a histogram of measurements. The resulting approximations are then incorporated into a Bayesiaan classification procedure for which the Bayes decision regions and the probability of misclassification is readily computed. Some preliminary numerical results are presented to illustrate the method.
    Keywords: NUMERICAL ANALYSIS
    Type: Proc. of the 2nd Ann. Symp. on Math. Pattern Recognition and Image Analysis Program; p 137-163
    Format: text
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  • 2
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    Concerning the numerical solution of differential equations. (1966)
    In:  Other Sources
    Details
    Publication Date: 2019-05-30
    Description: Step size for numerical solution of differential equation without violating stability region constraint
    Keywords: MATHEMATICS
    Type: MATHEMATICS OF COMPUTATION
    Format: text
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  • 3
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    Spline Classification Methods (1983)
    In:  CASI
    Details
    Publication Date: 2014-09-10
    Description: The use of spline functions in the development of classification algorithms is discussed. A method is formulated for producing spline approximations to univariate density functions when each density function is described by a histogram of measurements. The resulting approximations are then incorporated into a Bayesian classification procedure for which the probability of misclassification can be readily computed. Some preliminary numerical results are presented to illustrate the method.
    Keywords: NUMERICAL ANALYSIS
    Type: Proc. of the NASA Symp. on Math. Pattern Recognition and Image Analysis; p 167-190
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  • 4
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    Linear feature selection with applications (1979)
    In:  Other Sources
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    Publication Date: 2019-06-27
    Description: Several ways in which feature selection techniques were used in LACIE are discussed. In all cases, the methods require some a priori information and assumptions; in most, the classification procedure (Bayes optimal) was chosen in advance. The transformations used for dimensionality reduction are linear, that is, the variables in feature space are always linear combinations of the original measurements. Several numerically tractable criteria developed for LACIE, which provide information about the probability of misclassification, are discussed. Recent results on linear feature selection techniques are included. Their use in LACIE is discussed. Related open questions are mentioned.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: NASA. Johnson Space Center Proc. of Tech. Sessions, Vol. 1 and 2; p 691-703
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  • 5
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    The Cramer-Rao lower bound as a criteria for evaluating a large data reduction system such as LACIE (1979)
    In:  Other Sources
    Details
    Publication Date: 2019-06-27
    Description: There are no author-identified significant results in this report.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: REPT-21 , AgRISTARS: A Joint Program for Agriculture and Resource Inventory Surveys Through Aerospace Remote Sensing; 24 p
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  • 6
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    The easy remote sensing problem (1979)
    In:  Other Sources
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    Publication Date: 2019-06-27
    Description: There are no author-identified significant results in this report.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: REPT-20 , AgRISTARS: A Joint Program for Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing; 52 p
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  • 7
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    Distance preserving linear feature selection (1979)
    In:  Other Sources
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    Publication Date: 2019-06-27
    Description: There are no author-identified significant results in this report.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: REPT-19 , AgRISTARS: A Joint Program for Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing; 22 p
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  • 8
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    AgRISTARS: A joint program for agriculture and resources inventory surveys through aerospace remote sensing. Development and evaluation of clustering procedures (1979)
    In:  CASI
    Details
    Publication Date: 2019-06-27
    Description: There are no author-identified significant results in this report.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E80-10079 , NASA-CR-160427 , SR-T9-00402
    Format: application/pdf
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  • 9
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    Basic research planning in mathematical pattern recognition and image analysis (1981)
    In:  CASI
    Details
    Publication Date: 2019-06-28
    Description: Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: NASA-CR-160946
    Format: application/pdf
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  • 10
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    LFSPMC: Linear feature selection program using the probability of misclassification (1975)
    In:  CASI
    Details
    Publication Date: 2019-06-27
    Description: The computational procedure and associated computer program for a linear feature selection technique are presented. The technique assumes that: a finite number, m, of classes exists; each class is described by an n-dimensional multivariate normal density function of its measurement vectors; the mean vector and covariance matrix for each density function are known (or can be estimated); and the a priori probability for each class is known. The technique produces a single linear combination of the original measurements which minimizes the one-dimensional probability of misclassification defined by the transformed densities.
    Keywords: NUMERICAL ANALYSIS
    Type: NASA-CR-141878 , REPT-3
    Format: application/pdf
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