Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Nir Gorelik"'
Publikováno v:
Journal of Electrical and Computer Engineering, Vol 2012 (2012)
Accurate covariance matrix estimation for high-dimensional data can be a difficult problem. A good approximation of the covariance matrix needs in most cases a prohibitively large number of pixels, that is, pixels from a stationary section of the ima
Externí odkaz:
https://doaj.org/article/ae1f5ba1a31e440fa0ccf84edb0b46a9
Publikováno v:
MOEMS and Miniaturized Systems XX.
MEMS Mirrors provide a great way to spatially scan light and is being used for a wide range of applications such as raster scanning RGB light for Display Engines or scanning infra-red light for depth cameras (3D sensing) by using structured light or
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b640b0307e09eced2fd0bb9018e6189a
https://doi.org/10.1117/12.2577623
https://doi.org/10.1117/12.2577623
Publikováno v:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII.
Accurate covariance matrix estimation for high dimensional data can be a difficult problem. A good approximation of the covariance matrix needs in most cases a prohibitively large number of pixels, i.e. pixels from a stationary section of the image w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36bdcc341575e3e230ca5a2092d76f6f
https://doi.org/10.1117/12.915310
https://doi.org/10.1117/12.915310
Publikováno v:
Journal of Electrical and Computer Engineering, Vol 2012 (2012)
Accurate covariance matrix estimation for high-dimensional data can be a difficult problem. A good approximation of the covariance matrix needs in most cases a prohibitively large number of pixels, that is, pixels from a stationary section of the ima
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2fc30c2633b9c7fb6fab7c624523b480
Autor:
Véronique Achard, Nir Gorelik, Dirk Borghys, E. Schweicher, Christiaan Perneel, Stanley R. Rotman
Publikováno v:
2011 XXXth URSI General Assembly and Scientific Symposium.
Anomaly detection in hyperspectral data has received a lot of attention for various applications. The aim of anomaly detection is to detect pixels in the hyperspectral datacube whose spectra differ significantly from the background spectra. In anomal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9bb2488b9f90f37229e8e756c985ba2e
https://doi.org/10.1109/ursigass.2011.6050650
https://doi.org/10.1109/ursigass.2011.6050650