M. Ergul Et Al. , "Effective training set sampling strategy for SVDD anomaly detection in hyperspectral imagery," 20th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery , vol.9088, Maryland, United States Of America, 2014
Ergul, M. Et Al. 2014. Effective training set sampling strategy for SVDD anomaly detection in hyperspectral imagery. 20th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery , (Maryland, United States Of America).
Ergul, M., Sen, N., & Okman, O. E., (2014). Effective training set sampling strategy for SVDD anomaly detection in hyperspectral imagery . 20th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery, Maryland, United States Of America
Ergul, Mustafa, Nigar Sen, And O. Erman Okman. "Effective training set sampling strategy for SVDD anomaly detection in hyperspectral imagery," 20th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery, Maryland, United States Of America, 2014
Ergul, Mustafa Et Al. "Effective training set sampling strategy for SVDD anomaly detection in hyperspectral imagery." 20th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery , Maryland, United States Of America, 2014
Ergul, M. Sen, N. And Okman, O. E. (2014) . "Effective training set sampling strategy for SVDD anomaly detection in hyperspectral imagery." 20th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery , Maryland, United States Of America.
@conferencepaper{conferencepaper, author={Mustafa Ergul Et Al. }, title={Effective training set sampling strategy for SVDD anomaly detection in hyperspectral imagery}, congress name={20th SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery}, city={Maryland}, country={United States Of America}, year={2014}}