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Verlag: Morgan & Claypool Publishers, 2014
ISBN 10: 162705507XISBN 13: 9781627055079
Anbieter: HPB-Red, Dallas, TX, USA
Buch
Paperback. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!.
Verlag: Morgan & Claypool Publishers, 2014
ISBN 10: 162705507XISBN 13: 9781627055079
Anbieter: suffolkbooks, Center moriches, NY, USA
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Soft Cover. Zustand: new.
Verlag: Springer International Publishing Jun 2014, 2014
ISBN 10: 3031003942ISBN 13: 9783031003943
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch Print-on-Demand
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Augmented reality (AR) systems are often used to superimpose virtual objects or information on a scene to improve situational awareness. Delays in the display system or inaccurate registration of objects destroy the sense of immersion a user experiences when using AR systems. AC electromagnetic trackers are ideal for these applications when combined with head orientation prediction to compensate for display system delays. Unfortunately, these trackers do not perform well in environments that contain conductive or ferrous materials due to magnetic field distortion without expensive calibration techniques. In our work we focus on both the prediction and distortion compensation aspects of this application, developing a 'small footprint' predictive filter for display lag compensation and a simplified calibration system for AC magnetic trackers. In the first phase of our study we presented a novel method of tracking angular head velocity from quaternion orientation using an Extended Kalman Filter in both single model (DQEKF) and multiple model (MMDQ) implementations. In the second phase of our work we have developed a new method of mapping the magnetic field generated by the tracker without high precision measurement equipment. This method uses simple fixtures with multiple sensors in a rigid geometry to collect magnetic field data in the tracking volume. We have developed a new algorithm to process the collected data and generate a map of the magnetic field distortion that can be used to compensate distorted measurement data. Table of Contents: List of Tables / Preface / Acknowledgments / Delta Quaternion Extended Kalman Filter / Multiple Model Delta Quaternion Filter / Interpolation Volume Calibration / Conclusion / References / Authors' Biographies 192 pp. Englisch.
Verlag: CRC Press 2020-09-30, Boca Raton, 2020
ISBN 10: 0367656345ISBN 13: 9780367656348
Anbieter: Blackwell's, London, Vereinigtes Königreich
Buch
paperback. Zustand: New. Language: ENG.
Verlag: Springer International Publishing, 2014
ISBN 10: 3031003942ISBN 13: 9783031003943
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Augmented reality (AR) systems are often used to superimpose virtual objects or information on a scene to improve situational awareness. Delays in the display system or inaccurate registration of objects destroy the sense of immersion a user experiences when using AR systems. AC electromagnetic trackers are ideal for these applications when combined with head orientation prediction to compensate for display system delays. Unfortunately, these trackers do not perform well in environments that contain conductive or ferrous materials due to magnetic field distortion without expensive calibration techniques. In our work we focus on both the prediction and distortion compensation aspects of this application, developing a 'small footprint' predictive filter for display lag compensation and a simplified calibration system for AC magnetic trackers. In the first phase of our study we presented a novel method of tracking angular head velocity from quaternion orientation using an Extended KalmanFilter in both single model (DQEKF) and multiple model (MMDQ) implementations. In the second phase of our work we have developed a new method of mapping the magnetic field generated by the tracker without high precision measurement equipment. This method uses simple fixtures with multiple sensors in a rigid geometry to collect magnetic field data in the tracking volume. We have developed a new algorithm to process the collected data and generate a map of the magnetic field distortion that can be used to compensate distorted measurement data. Table of Contents: List of Tables / Preface / Acknowledgments / Delta Quaternion Extended Kalman Filter / Multiple Model Delta Quaternion Filter / Interpolation Volume Calibration / Conclusion / References / Authors' Biographies.
Verlag: CRC Press, 2017
ISBN 10: 1138030198ISBN 13: 9781138030190
Anbieter: Basi6 International, Irving, TX, USA
Buch
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Verlag: Springer, Berlin|Springer International Publishing|Morgan & Claypool|Springer, 2014
ISBN 10: 3031003942ISBN 13: 9783031003943
Anbieter: moluna, Greven, Deutschland
Buch Print-on-Demand
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Augmented reality (AR) systems are often used to superimpose virtual objects or information on a scene to improve situational awareness. Delays in the display system or inaccurate registration of objects destroy the sense of immersion a user experiences whe.
Verlag: CRC Pr I Llc, 2020
ISBN 10: 0367656345ISBN 13: 9780367656348
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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Paperback. Zustand: Brand New. 204 pages. 9.25x6.14x0.47 inches. In Stock.
Verlag: Springer, 2013
ISBN 10: 3642415083ISBN 13: 9783642415081
Anbieter: booksXpress, Bayonne, NJ, USA
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Hardcover. Zustand: new.
Verlag: Taylor & Francis Ltd, 2020
ISBN 10: 0367656345ISBN 13: 9780367656348
Anbieter: Buchpark, Trebbin, Deutschland
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Zustand: Wie neu. Zustand: Wie neu | Seiten: 190.
Verlag: Taylor & Francis Group, 2017
ISBN 10: 1138030198ISBN 13: 9781138030190
Anbieter: Books Puddle, New York, NY, USA
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Zustand: New. pp. 168.
Verlag: Springer, 2016
ISBN 10: 3662510642ISBN 13: 9783662510643
Anbieter: booksXpress, Bayonne, NJ, USA
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Soft Cover. Zustand: new.
Verlag: CRC Press, 2020
ISBN 10: 0367656345ISBN 13: 9780367656348
Anbieter: moluna, Greven, Deutschland
Buch Print-on-Demand
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Cesar Barrios received a B.S. (1999) and an M.S. (2001) in electrical engineering from the New Jersey Institute of Technology, and a Ph.D. degree (2014) in electrical engineering from the University of Vermont. He worked for IBM after graduating with his.
Verlag: Taylor & Francis Group, 2017
ISBN 10: 1138030198ISBN 13: 9781138030190
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
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Zustand: New. pp. 168.
Verlag: Springer, 2013
ISBN 10: 3642415083ISBN 13: 9783642415081
Anbieter: Lucky's Textbooks, Dallas, TX, USA
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Zustand: New.
Verlag: Springer, 2013
ISBN 10: 3642415083ISBN 13: 9783642415081
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Buch Print-on-Demand
Hardcover. Zustand: Brand New. 1st edition. 167 pages. 9.25x6.25x0.50 inches. This item is printed on demand.
Verlag: Springer Berlin Heidelberg Nov 2013, 2013
ISBN 10: 3642415083ISBN 13: 9783642415081
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch Print-on-Demand
Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin.In the first chapter following the Introduction to this book, we review three prediction approaches of respiratory motion: model-based methods, model-free heuristic learning algorithms, and hybrid methods. In the following chapter, we present a phantom study-prediction of human motion with distributed body sensors-using a Polhemus Liberty AC magnetic tracker. Next we describe respiratory motion estimation with hybrid implementation of extended Kalman filter. The given method assigns the recurrent neural network the role of the predictor and the extended Kalman filter the role of the corrector. After that, we present customized prediction of respiratory motion with clustering from multiple patient interactions. For the customized prediction, we construct the clustering based on breathing patterns of multiple patients using the feature selection metrics that are composed of a variety of breathing features. We have evaluated the new algorithm by comparing the prediction overshoot and the tracking estimation value. The experimental results of 448 patients' breathing patterns validated the proposed irregular breathing classifier in the last chapter. 180 pp. Englisch.
Verlag: Springer Berlin Heidelberg Aug 2016, 2016
ISBN 10: 3662510642ISBN 13: 9783662510643
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Buch Print-on-Demand
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin.In the first chapter following the Introduction to this book, we review three prediction approaches of respiratory motion: model-based methods, model-free heuristic learning algorithms, and hybrid methods. In the following chapter, we present a phantom study-prediction of human motion with distributed body sensors-using a Polhemus Liberty AC magnetic tracker. Next we describe respiratory motion estimation with hybrid implementation of extended Kalman filter. The given method assigns the recurrent neural network the role of the predictor and the extended Kalman filter the role of the corrector. After that, we present customized prediction of respiratory motion with clustering from multiple patient interactions. For the customized prediction, we construct the clustering based on breathing patterns of multiple patients using the feature selection metrics that are composed of a variety of breathing features. We have evaluated the new algorithm by comparing the prediction overshoot and the tracking estimation value. The experimental results of 448 patients' breathing patterns validated the proposed irregular breathing classifier in the last chapter. 180 pp. Englisch.
Verlag: CRC Press, 2017
ISBN 10: 1138030198ISBN 13: 9781138030190
Anbieter: GreatBookPrices, Columbia, MD, USA
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Zustand: New.
Verlag: Wiley, 2015
ISBN 10: 111901932XISBN 13: 9781119019329
Anbieter: GreatBookPrices, Columbia, MD, USA
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Zustand: As New. Unread book in perfect condition.
Verlag: Wiley, 2015
ISBN 10: 111901932XISBN 13: 9781119019329
Anbieter: Lucky's Textbooks, Dallas, TX, USA
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Zustand: New.
Verlag: Wiley, 2015
ISBN 10: 111901932XISBN 13: 9781119019329
Anbieter: GreatBookPrices, Columbia, MD, USA
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Zustand: New.
Verlag: Wiley, 2015
ISBN 10: 111901932XISBN 13: 9781119019329
Anbieter: Brook Bookstore, Milano, MI, Italien
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Zustand: new.
Verlag: Wiley, 2015
ISBN 10: 111901932XISBN 13: 9781119019329
Anbieter: GreatBookPricesUK, Castle Donington, DERBY, Vereinigtes Königreich
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Zustand: New.
Verlag: CRC Press, 2017
ISBN 10: 1138030198ISBN 13: 9781138030190
Anbieter: GreatBookPrices, Columbia, MD, USA
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Zustand: As New. Unread book in perfect condition.
Verlag: Wiley 2015-04-13, Hoboken, New Jersey, 2015
ISBN 10: 111901932XISBN 13: 9781119019329
Anbieter: Blackwell's, London, Vereinigtes Königreich
Buch
hardback. Zustand: New. Language: ENG.
Verlag: Springer Berlin Heidelberg, 2013
ISBN 10: 3642415083ISBN 13: 9783642415081
Anbieter: moluna, Greven, Deutschland
Buch Print-on-Demand
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in Prediction and Classification of Respiratory MotionIntroduction to recent algorithms describing respiratory motionWritten by experts in the fieldThis book describes recent radiotherapy technologies including to.
Verlag: Springer Berlin Heidelberg, 2016
ISBN 10: 3662510642ISBN 13: 9783662510643
Anbieter: moluna, Greven, Deutschland
Buch Print-on-Demand
Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Recent research in Prediction and Classification of Respiratory MotionIntroduction to recent algorithms describing respiratory motionWritten by experts in the fieldThis book describes recent radiotherapy technologies including to.
Verlag: Springer Berlin Heidelberg, 2013
ISBN 10: 3642415083ISBN 13: 9783642415081
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin.In the first chapter following the Introduction to this book, we review three prediction approaches of respiratory motion: model-based methods, model-free heuristic learning algorithms, and hybrid methods. In the following chapter, we present a phantom study-prediction of human motion with distributed body sensors-using a Polhemus Liberty AC magnetic tracker. Next we describe respiratory motion estimation with hybrid implementation of extended Kalman filter. The given method assigns the recurrent neural network the role of the predictor and the extended Kalman filter the role of the corrector. After that, we present customized prediction of respiratory motion with clustering from multiple patient interactions. For the customized prediction, we construct the clustering based on breathing patterns of multiple patients using the feature selection metrics that are composed of a variety of breathing features. We have evaluated the new algorithm by comparing the prediction overshoot and thetracking estimation value. The experimental results of 448 patients' breathing patterns validated the proposed irregular breathing classifier in the last chapter.