Jain ronak (7 Ergebnisse)

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  • Sprache: Englisch

    Verlag: Notion Press, 2016

    9386073587 / 9789386073587

    • Softcover

    Anbieter: California Books, Miami, FL, USACalifornia Books

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    Zustand: Neu

    EUR 15,06

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    Zustand: New.

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing, 2018

    6137344266 / 9786137344262

    • Softcover

    Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books

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    Zustand: Neu

    EUR 64,13

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    Paperback. Zustand: Brand New. 72 pages. 8.66x5.91x0.17 inches. In Stock.

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing, 2018

    6137344266 / 9786137344262

    • Softcover

    Anbieter: preigu, Osnabrück, Deutschlandpreigu

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    Zustand: Neu

    EUR 33,30

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    Taschenbuch. Zustand: Neu. Study of Mineral Mapping Techniques using Airborne Hyperspectral Data | Exploring the potential of AVIRIS-NG for Mineral Identification | Ronak Jain (u. a.) | Taschenbuch | 72 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786137344262 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing Feb 2018, 2018

    6137344266 / 9786137344262

    • Softcover
    • Print-on-Demand

    Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, DeutschlandBuchWeltWeit Ludwig Meier e.K.

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    Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Geology is a science deal with the minerals and rocks majorly. Hyperspectral data is used in the geology domain for mineral identification and mapping. Because of its high spatial as well as high spectral resolution. The main objective is to identify the different minerals on the earth crust using different mineral mapping algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using AVIRIS-NG data and conclude the better algorithm for mineral mapping. For identification of a different kind of minerals, spectral analysis is performed. Imagery pixel spectrum is matched with predefined or unique (pure) spectra for the mineral detection. SAM algorithm mainly computes the angle between the pixel spectra and reference spectra. The SFF compares the continuum removed spectrum of the image with the continuum removed reference spectrum and operated the least square fitting. MTMF is a combination of two different algorithms and works on the MNF transformed data for estimation of abundance of minerals along with the identification of the false positive. MTMF perform well and gives better results for mineral mapping. 72 pp. Englisch.

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing, 2018

    6137344266 / 9786137344262

    • Softcover
    • Print-on-Demand

    Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH

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    Zustand: Neu

    EUR 38,45

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    Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Geology is a science deal with the minerals and rocks majorly. Hyperspectral data is used in the geology domain for mineral identification and mapping. Because of its high spatial as well as high spectral resolution. The main objective is to identify the different minerals on the earth crust using different mineral mapping algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using AVIRIS-NG data and conclude the better algorithm for mineral mapping. For identification of a different kind of minerals, spectral analysis is performed. Imagery pixel spectrum is matched with predefined or unique (pure) spectra for the mineral detection. SAM algorithm mainly computes the angle between the pixel spectra and reference spectra. The SFF compares the continuum removed spectrum of the image with the continuum removed reference spectrum and operated the least square fitting. MTMF is a combination of two different algorithms and works on the MNF transformed data for estimation of abundance of minerals along with the identification of the false positive. MTMF perform well and gives better results for mineral mapping.

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing, 2018

    6137344266 / 9786137344262

    • Softcover
    • Print-on-Demand

    Anbieter: moluna, Greven, Deutschlandmoluna

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    Zustand: Neu

    EUR 31,27

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    Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jain RonakRonak Jain is presently pursuing PhD from Mohanlal Sukhadia University, Rajasthan. He received his M.Sc.(2015) & M.Sc. Tech.(2016) in Geology from MLSU and Post-Graduate Diploma in Geoinformatics (2017) from Indian Institut.

  • Sprache: Englisch

    Verlag: LAP LAMBERT Academic Publishing Feb 2018, 2018

    6137344266 / 9786137344262

    • Softcover
    • Print-on-Demand

    Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschlandbuchversandmimpf2000

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    Zustand: Neu

    EUR 35,90

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    Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Geology is a science deal with the minerals and rocks majorly. Hyperspectral data is used in the geology domain for mineral identification and mapping. Because of its high spatial as well as high spectral resolution. The main objective is to identify the different minerals on the earth crust using different mineral mapping algorithms such as Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Mixture Tuned Matched Filtering (MTMF) using AVIRIS-NG data and conclude the better algorithm for mineral mapping. For identification of a different kind of minerals, spectral analysis is performed. Imagery pixel spectrum is matched with predefined or unique (pure) spectra for the mineral detection. SAM algorithm mainly computes the angle between the pixel spectra and reference spectra. The SFF compares the continuum removed spectrum of the image with the continuum removed reference spectrum and operated the least square fitting. MTMF is a combination of two different algorithms and works on the MNF transformed data for estimation of abundance of minerals along with the identification of the false positive. MTMF perform well and gives better results for mineral mapping.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 72 pp. Englisch.