Monteiro Sildomar (16 results)

- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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- Softcover
Seller: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
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£ 43.06
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Paperback or Softback. Condition: New. Automatic Hyperspectral Data Analysis. Book.

- Softcover
Seller: Rarewaves.com USA, London, LONDO, United KingdomRarewaves.com USA
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£ 44.67
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Paperback. Condition: New.

- Softcover
Seller: California Books, Miami, FL, U.S.A.California Books
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- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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£ 39.71
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Condition: New. In.

- Softcover
Seller: Chiron Media, Wallingford, United KingdomChiron Media
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PF. Condition: New.

- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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£ 39.70
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Condition: New.

- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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£ 38.31
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Taschenbuch. Condition: Neu. Automatic Hyperspectral Data Analysis | A machine learning approach to high dimensional feature extraction | Sildomar Monteiro | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2010 | VDM Verlag Dr. Müller | EAN 9783639255164 | Verantwortliche Person für die EU: OmniScriptum GmbH & Co. KG, Bahnhofstr. 28, 66111 Saarbrücken, info[at]akademikerverlag[dot]de | Anbieter: preigu. …

- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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£ 41.49
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Paperback. Condition: New.

- Softcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
Contact seller5-star sellerCondition: Used - As new
£ 111.99
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Condition: As New. Unread book in perfect condition.

- Softcover
Seller: Mispah books, Redhill, SURRE, United KingdomMispah books
Contact seller4-star sellerCondition: Used - As new
£ 104.00
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Paperback. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

- Softcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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£ 134.07
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Condition: As New. Unread book in perfect condition.

- Softcover
- Print on Demand
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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£ 44.02
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

- Softcover
- Print on Demand
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
Contact seller5-star sellerCondition: New
£ 41.56
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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.

- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
Contact seller5-star sellerCondition: New
£ 34.65
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Monteiro SildomarSildomar Monteiro is Research Fellow in the Australian Centre for Field Robotics at Sydney University. He was awarded a JSPS postdoctoral fellowship in 2007. His research areas include machine learning, computer visi.…

- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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£ 62.67
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Advances in spectroscopy sensors have allowed the acquisition of ever-increasing volumes of data from scenes, either remotely, by air- or space-borne devices, or locally, by hand-held spectrometers or stand-alone cameras. With this boom in the amount of data available has also come a greater need for extracting useful information efficiently and for developing automated methods for novel applications. Traditional approaches to spectral analysis often require a great deal of human effort and prior knowledge, and have difficulty in processing high dimensional data sets provided by new sensors. This book, therefore, provides an alternative approach to select relevant features from hyperspectral data utilizing machine learning to automate the analysis. The methods are developed in the context of two applications: in biomedical imaging and in precision agriculture. The techniques discussed should be useful to graduate students and researchers in computer science and engineering interested in hyperspectral imaging, remote sensing or optimization for high dimensional data.…