Koo Robert (31 results)

Condition: New.

Condition: New.

Soft cover. Condition: Fine. 1st Edition. ISSN # 0440-2316. From the collection of Robert Hershon.

Hardcover. Condition: Fine. Dust Jacket Condition: Fine. 341 pages.

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.

Condition: New.

Condition: New.

Condition: New.

Condition: New. Feature Extraction Using Principal and Independent Component Analysis aor Hyperspectral Imagery (Paperback or Softback).

Condition: New.

Condition: New. In.

Condition: New.

Paperback. Condition: 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).

paperback. Condition: New. In shrink wrap. Looks like an interesting title!

Buch. Condition: 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.

Condition: 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.

Condition: As New. Unread book in perfect condition.

Paperback. Condition: Like New. Like New. book.

Condition: As New. Unread book in perfect condition.

Taschenbuch. Condition: 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.

LeatherBound. Condition: New. BOOKS ARE EXEMPT FROM IMPORT DUTIES AND TARIFFS; NO EXTRA CHARGES APPLY. Leatherbound edition. Condition: New. Leather Binding on Spine and Corners with Golden leaf printing on spine. Bound in genuine leather with Satin ribbon page markers and Spine with raised gilt bands. Pages: 160. A perfect gift for your loved ones. Reprinted from 1974 edition. NO changes have been made to the original text. This is NOT a retyped or an ocr'd reprint. Illustrations, Index, if any, are included in black and white. Each page is checked manually before printing. As this print on demand book is reprinted from a very old book, there could be some missing or flawed pages, but we always try to make the book as complete as possible. Fold-outs, if any, are not part of the book. If the original book was published in multiple volumes then this reprint is of only one volume, not the whole set. IF YOU WISH TO ORDER PARTICULAR VOLUME OR ALL THE VOLUMES YOU CAN CONTACT US. Resized as per current standards. Sewing binding for longer life, where the book block is actually sewn (smythe sewn/section sewn) with thread before binding which results in a more durable type of binding. Language: English Pages: 160.

Condition: Bueno. 1st ed. 22x33. 276pp. Publisher's boards. Tela editorial. Publisher's boards. Tela editorial.

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.

LeatherBound. Condition: New. BOOKS ARE EXEMPT FROM IMPORT DUTIES AND TARIFFS; NO EXTRA CHARGES APPLY. LeatherBound edition. Condition: New. Reprinted from 1953 edition. Leather Binding on Spine and Corners with Golden leaf printing on spine. Bound in genuine leather with Satin ribbon page markers and Spine with raised gilt bands. A perfect gift for your loved ones. Pages: 166 NO changes have been made to the original text. This is NOT a retyped or an ocr'd reprint. Illustrations, Index, if any, are included in black and white. Each page is checked manually before printing. As this print on demand book is reprinted from a very old book, there could be some missing or flawed pages, but we always try to make the book as complete as possible. Fold-outs, if any, are not part of the book. If the original book was published in multiple volumes then this reprint is of only one volume, not the whole set. Sewing binding for longer life, where the book block is actually sewn (smythe sewn/section sewn) with thread before binding which results in a more durable type of binding. Pages: 166.

Condition: New. Print on Demand.

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condition: New. PRINT ON DEMAND.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condition: new. Paperback. 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.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.