robert koo (6 Ergebnisse)

Abstracts of Articles 1 à 9 in : University of Washington Publications in Fisheries, New Series, Volume I, "Studies of Alaska Red Salmon", University of Washington Press, 1962, Contributions No. 105 à 113, College of Fisheries, University of Washington, 18 pages de 15,50x23,50 cm Bon état - Pour les envois hors de France, la tafication «livre & brochure» pour les frais de port a disparue.Les frais de port annoncés correspondent à une moyenne. Ils seront calculés au plus juste en fonction du poids de votre article.

Paperback. Zustand: Near Fine. Chuang, Che; Chen, Cheng-Hsiung [Robert], Yang, Hsing-Shen, Koo, Chung-Kuang [in] (illustrator). First Edition. Exhibition Catalog With Color And B/W Reproductions. Inscribed "To My Dear Friend Mr. ----- H. S. Yang 1973.8.6". Near Fine. Signed by Illustrator(s).

Buch. Zustand: Neu. Neuware - Hyperspectral imagery (HSI) analysis is frequently employed by the Department of Defense for the purpose of classifying objects within an image as a form of target detection. In this research a robust Two-Phase Filtering Independent Component Analysis (ICA) Target Detection Method is proposed and validated. This new method resolves two main challenges encountered when implementing target detection methods using ICA, a high order statistics feature extraction (FE) method. The first challenge is the high computational demand imposed by the large volume of data associated with HSI during the FE process. To alleviate the effort required for ICA data processing, principal component analysis (PCA), a classical second order statistics method, is used for data reduction. Furthermore, the performance of using PCA under classification is compared against recently developed supervised FE techniques. The second challenge arises during the feature selection (FS) phase after the statistically independent components have been extracted. Current ICA target FS techniques have shown to be either unreliable or require significant user-intervention. A reliable FS process is essential in automating the target detection process. This proposed method uses ICA to extract independent features from the retained principal components, and is followed by an unsupervised target FS with a two-phase filtering process using kurtosis and mean silhouette values. This method achieved promising results when tested against a wide range of benchmark images.

Zustand: New. KlappentextrnrnHyperspectral imagery (HSI) analysis is frequently employed by the Department of Defense for the purpose of classifying objects within an image as a form of target detection. In this research a robust Two-Phase Filtering Independe.

Taschenbuch. Zustand: Neu. Neuware - Hyperspectral imagery (HSI) analysis is frequently employed by the Department of Defense for the purpose of classifying objects within an image as a form of target detection. In this research a robust Two-Phase Filtering Independent Component Analysis (ICA) Target Detection Method is proposed and validated. This new method resolves two main challenges encountered when implementing target detection methods using ICA, a high order statistics feature extraction (FE) method. The first challenge is the high computational demand imposed by the large volume of data associated with HSI during the FE process. To alleviate the effort required for ICA data processing, principal component analysis (PCA), a classical second order statistics method, is used for data reduction. Furthermore, the performance of using PCA under classification is compared against recently developed supervised FE techniques. The second challenge arises during the feature selection (FS) phase after the statistically independent components have been extracted. Current ICA target FS techniques have shown to be either unreliable or require significant user-intervention. A reliable FS process is essential in automating the target detection process. This proposed method uses ICA to extract independent features from the retained principal components, and is followed by an unsupervised target FS with a two-phase filtering process using kurtosis and mean silhouette values. This method achieved promising results when tested against a wide range of benchmark images.

104 pp.; 21.5 x 10.7 cm.; glue bound; black-and-white; edition size 5000; unsigned and unnumbered; offset-printed Exhibition catalogue published in conjunction with the traveling show "do it," conceived and curated and with an introduction by Hans-Ulrich Obrist. Essay by Bruce Altshuler. Artists in the museum portion of the exhibit include Andrew Bolton, Joan Brossa, Critical Art Ensemble, Jimmie Durham, Maria Eichhorn, Hans-Peter Feldmann, Paul-Armand Gette, Felix Gonzalez-Torres, Joseph Grigely, Ulrike Grossarth, Shere Hite, Fabrice Hybert, Ilya Kabakov, Mike Kelley, Alison Knowles, Koo Jeong-a, Bertrand Lavier, Siobhan Liddell, Eva Marisaldi, Chris Marker, Yoko Ono, Michelangelo Pistoletto, Emilio Prini, Jason Rhoades, Rupert Sheldrake, Andreas Slominski, Bruce Sterling, Rirkrit Tiravanija, Lawrence Weiner, Erwin Wurm, Marina Abramovic, Dara Birnbaum, Gilbert & George, Liam Gillick, Douglas Gordon, Dan Graham, Marie-Ange Guilleminot, María Teresa Hincapié, Allan Kaprow, Ben Kinmont, Jiri Kolar, Annette Messager, Eileen Myles, Pepón Osorio, Steven Pippin, Pipilotti Rist, Nancy Spero, Rosemarie Trockel and Franz West. Artists included in do it (tv) broadcast on Austrian television include Gilbert & George, Leon Golub, Douglas Gordon, Marie-Ange Guilleminot, Shere Hite, Robert Jelinek, Ilya Kabakov, Jonas Mekas, Eileen Myles, Yoko Ono, Steven Pippin, Michelangelo Pistoletto, Michael Smith, Nancy Spero, Rirkrit Tiravanija, Lawrence Weiner, Christian Boltanski, John Baldessari, and Erwin Wurm. Very Good. Light rubbing of covers and fading at spine. Contents clean and unmarked.