Zobrazeno 1 - 10
of 151
pro vyhledávání: '"Landgrebe, David A."'
Autor:
Biehl, Larry *, Landgrebe, David
Publikováno v:
In Computers and Geosciences 2002 28(10):1153-1159
Autor:
Landgrebe, David
Publikováno v:
Journal of Terrestrial Observation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::bbf3609e913b2c469fcca055f418b5c8
http://docs.lib.purdue.edu/jto/vol1/iss1/art3
http://docs.lib.purdue.edu/jto/vol1/iss1/art3
Autor:
Dundar, Mehmet M., Landgrebe, David
Publikováno v:
Department of Electrical and Computer Engineering Technical Reports
In hyperspectral data materials of practical interest usually exist in a number of states and are observed in a number of conditions of illumination. It is thus necessary to characterize them not with a single spectral response but with a family of r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::afd50c00daafefeda394635a7422f701
http://docs.lib.purdue.edu/ecetr/149
http://docs.lib.purdue.edu/ecetr/149
Autor:
Jackson, Qiong Zhang, Landgrebe, David
Publikováno v:
Department of Electrical and Computer Engineering Technical Reports
In a typical supervised classification procedure the availability of training samples has a fundamental effect on classifier performance. For a fixed number of training samples classifier performance is degraded as the number of dimensions (features)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::c52593b2b200fc6d5b416dec85a122c3
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1010&context=ecetr
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1010&context=ecetr
Autor:
Kuo, Bor-Chen, Landgrebe, David
Publikováno v:
Department of Electrical and Computer Engineering Technical Reports
For hyperspectral data classification, the avoidance of singularity of covariance estimates or excessive near singularity estimation error due to limited training data is a key problem. This study is intended to solve problem via regularized covarian
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::f00dfdbc3ce3e7c6a3cff58f71dc6a79
http://docs.lib.purdue.edu/ecetr/10
http://docs.lib.purdue.edu/ecetr/10
Publikováno v:
Repositório Institucional da UFRGS
Universidade Federal do Rio Grande do Sul (UFRGS)
instacron:UFRGS
Universidade Federal do Rio Grande do Sul (UFRGS)
instacron:UFRGS
It is well known that high-dimensional image data allows for the separation of classes that are spectrally very similar, i.e., possess nearly equal first-order statistics, provided that their second-order statistics differ significantly. The aim of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3056::ab732908b2e44d47740cabb8f08a57ae
Autor:
Hsieh, Pi-Fuei, Landgrebe, David
Publikováno v:
Department of Electrical and Computer Engineering Technical Reports
Multispectral sensors have been used to gather data about the Earth's surface since the 1960's. Data analysis methods for multispectral data with less than 20 or so spectral bands have been studied and have given satisfactory results. As opposed to s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::0880a7bea60ad26dea1238b61912f6a9
http://docs.lib.purdue.edu/ecetr/52
http://docs.lib.purdue.edu/ecetr/52
Autor:
Tadjudin, Saldju, Landgrebe, David
Publikováno v:
Department of Electrical and Computer Engineering Technical Reports
An important problem in pattern recognition is the effect of limited training samples on classification performance. When the ratio of the number of training samples to the dimensionality is small, parameter estimates become highly variable, causing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::bb0edd6c67046371ef876c7ceed00200
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1055&context=ecetr
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1055&context=ecetr
Autor:
Jimenez, Luis O., Landgrebe, David
Publikováno v:
Department of Electrical and Computer Engineering Technical Reports
The irecent development of more sophisticated sensors for remote sensing systems enables the measurement of radiation in many more spectral intervals than previous possible. An example of this technology is the AVlRlS system., which collects image da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::38935a744a5f2d67008008272288e39d
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1103&context=ecetr
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1103&context=ecetr
Autor:
Safavian, S. Rasoul, Landgrebe, David
Publikováno v:
Department of Electrical and Computer Engineering Technical Reports
Bayesian inference and decision making requires elici1:ation of prior probabilities and sampling distributions. In many applica~tions such as exploratory data analysis, however, it may not be possible to construct the prior probabilities or the sampl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______540::789ec2eab5f3c212db57ee951cdd0622
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1142&context=ecetr
http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1142&context=ecetr