De shaunak (9 risultati)
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Da: preigu, Osnabrück, Germaniapreigu
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EUR 64,20
EUR 70,00 spedizioneSpedito da Germania a U.S.A.Quantità: 5 disponibili
Taschenbuch. Condizione: Neu. Applications of Deep Learning to Radar Polarimetry | A Physics First Approach to Machine Learning in Radar Earth Observation Applications | Shaunak de | Taschenbuch | 212 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786139815999 | Verantwortliche Person für die EU: preigu GmbH & Co.… KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 137,42
EUR 11,68 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: Brand New. 212 pages. 8.66x5.91x0.48 inches. In Stock.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 76,90
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Radar remote sensing has made significant technological and scientific advances in the past few years. Sensors and constellations are able to acquire high resolution, polarimetric, wide swath data with high temporal repetivity. Thi…s has lead to an exponential increase in the volume of data available. With more temporally dense constellations planned in the near future, it is imperative that automated techniques based on machine learning algorithms be developed that are able to take advantage of all the acquired data and convert latent information to actionable knowledge. However, the use of indiscriminate machine learning techniques can be problematic since there is no guarantee that the learned model makes sense from a physical standpoint. Advanced neural network techniques, collectively called 'deep leaning' algorithms have demonstrated the ability to self-learn features from a data-volume, greatly reducing the need for time-consuming feature tuning. In this book, novel deep learning algorithms and architectures are detailed for various earth observation applications using fully polarimetric SAR data based, and constrained by the principles of scattering physics. 212 pp. Englisch.
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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 84,90
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 212 pp. Englisch.
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Da: moluna, Greven, Germaniamoluna
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 61,85
EUR 48,99 spedizioneSpedito da Germania a U.S.A.Quantità: Più di 20 disponibili
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: De ShaunakDr Shaunak De received the B.Eng. in electronics from the University of Mumbai in 2012 (gold medalist) and the PhD from Indian Institute of Technology Bombay in 2018. He s worked extensively…in the field of remote sensing, .
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 76,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Radar remote sensing has made significant technological and scientific advances in the past few years. Sensors and constellations are able to acquire high resolution, polarimetric, wide swath data with high temporal repetivity. This ha…s lead to an exponential increase in the volume of data available. With more temporally dense constellations planned in the near future, it is imperative that automated techniques based on machine learning algorithms be developed that are able to take advantage of all the acquired data and convert latent information to actionable knowledge. However, the use of indiscriminate machine learning techniques can be problematic since there is no guarantee that the learned model makes sense from a physical standpoint. Advanced neural network techniques, collectively called 'deep leaning' algorithms have demonstrated the ability to self-learn features from a data-volume, greatly reducing the need for time-consuming feature tuning. In this book, novel deep learning algorithms and architectures are detailed for various earth observation applications using fully polarimetric SAR data based, and constrained by the principles of scattering physics.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 212 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 77,82
EUR 61,67 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Radar remote sensing has made significant technological and scientific advances in the past few years. Sensors and constellations are able to acquire high resolution, polarimetric, wide swath data with high temporal repetivity. This has… lead to an exponential increase in the volume of data available. With more temporally dense constellations planned in the near future, it is imperative that automated techniques based on machine learning algorithms be developed that are able to take advantage of all the acquired data and convert latent information to actionable knowledge. However, the use of indiscriminate machine learning techniques can be problematic since there is no guarantee that the learned model makes sense from a physical standpoint. Advanced neural network techniques, collectively called 'deep leaning' algorithms have demonstrated the ability to self-learn features from a data-volume, greatly reducing the need for time-consuming feature tuning. In this book, novel deep learning algorithms and architectures are detailed for various earth observation applications using fully polarimetric SAR data based, and constrained by the principles of scattering physics.
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- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 84,90
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Radar remote sensing has made significant technological and scientific advances in the past few years. Sensors and constellations are able to acquire high resolution, polarimetric, wide swath data with high temporal repetivity. This ha…s lead to an exponential increase in the volume of data available. With more temporally dense constellations planned in the near future, it is imperative that automated techniques based on machine learning algorithms be developed that are able to take advantage of all the acquired data and convert latent information to actionable knowledge. However, the use of indiscriminate machine learning techniques can be problematic since there is no guarantee that the learned model makes sense from a physical standpoint. Advanced neural network techniques, collectively called 'deep leaning' algorithms have demonstrated the ability to self-learn features from a data-volume, greatly reducing the need for time-consuming feature tuning. In this book, novel deep learning algorithms and architectures are detailed for various earth observation applications using fully polarimetric SAR data based, and constrained by the principles of scattering physics.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 212 pp. Englisch.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 85,92
EUR 61,67 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering.
