Order Total (1 Item Items):
Shipping Destination:
Pasricha Sudeep (133 results)
Skip to main search results
Search filters
Product Type
- All Product Types
- Books (133)
- Magazines & Periodicals (No further results match this refinement)
- Comics (No further results match this refinement)
- Sheet Music (No further results match this refinement)
- Art, Prints & Posters (No further results match this refinement)
- Photographs (No further results match this refinement)
- Maps (No further results match this refinement)
- Manuscripts & Paper Collectibles (No further results match this refinement)
Condition Learn more
- New (120)
- As New, Fine or Near Fine (7)
- Very Good or Good (4)
- Fair or Poor (No further results match this refinement)
- As Described (2)
Binding
Collectible Attributes
- First Edition (No further results match this refinement)
- Signed (No further results match this refinement)
- Dust Jacket (No further results match this refinement)
- Seller-Supplied Images (67)
- Not Print on Demand (87)
Language (1)
Free Shipping
Seller Location
Seller Rating
-
Condition: good. Fast Free Shipping â" Good condition. It may show normal signs of use, such as light writing, highlighting, or library markings, but all pages are intact and the book is fully readable. A solid, complete copy that's ready to enjoy.
-
hardcover. Condition: Very 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 limited writing/highlighting. We ship orders daily and Customer Service is our top priority!
-
hardcover. Condition: 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!
-
Condition: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.
-
Machine Learning for Indoor Localization and Navigation
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 61.39
US$ 16.01 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Condition: New. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped.
-
Condition: As New. Unread book in perfect condition.
-
On-Chip Communication Architectures: System on Chip Interconnect: Volume - (Systems on Silicon)
Language: English
Published by Morgan Kaufmann 2008-02-15, 2008
ISBN 10: 012373892X ISBN 13: 9780123738929
US$ 79.90
US$ 20.70 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardcover. Condition: New.
-
Condition: New. pp. 544.
-
Condition: New.
-
Condition: New.
-
US$ 90.88
US$ 20.04 shipping
Ships from United Kingdom to U.S.A.Quantity: 2 available
Add to basketHardcover. Condition: Brand New. illustrated edition. 536 pages. 9.50x8.00x1.50 inches. In Stock.
-
Machine Learning for Indoor Localization and Navigation (Paperback)
Language: English
Published by Springer International Publishing AG, Cham, 2024
ISBN 10: 3031267141 ISBN 13: 9783031267147
Paperback. Condition: new. Paperback. While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve theaccuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. In particular, the book:Provides comprehensive coverage of the application of machine learning to the domain of indoor localization;Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization;Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
-
Condition: New. 2023rd edition NO-PA16APR2015-KAP.
-
Condition: New. First edition Includes bibliographical references and index.
-
Silicon Photonics for High-Performance Computing and Beyond
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 97.79
US$ 20.04 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketCondition: As New. Unread book in perfect condition.
-
US$ 106.72
US$ 8.69 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketCondition: New.
-
Silicon Photonics for High-Performance Computing and Beyond
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 103.47
US$ 16.01 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Condition: New. pp. 544.
-
US$ 103.22
US$ 16.70 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Brand New. 582 pages. 9.25x6.10x9.25 inches. In Stock.
-
Silicon Photonics for High-Performance Computing and Beyond
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 103.43
US$ 20.04 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketCondition: New.
-
Condition: New. pp. 544.
-
Silicon Photonics for High-Performance Computing and Beyond
Language: English
Published by Taylor & Francis Ltd, 2024
ISBN 10: 1032122447 ISBN 13: 9781032122441
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 103.44
US$ 24.39 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
-
Condition: New.
-
Machine Learning for Indoor Localization and Navigation (Hardcover)
Language: English
Published by Springer International Publishing AG, Cham, 2023
ISBN 10: 3031267117 ISBN 13: 9783031267116
Hardcover. Condition: new. Hardcover. While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve theaccuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. In particular, the book:Provides comprehensive coverage of the application of machine learning to the domain of indoor localization;Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization;Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
-
Condition: New.
-
Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems
Seller: SKULIMA Wiss. Versandbuchhandlung, Westhofen, Germany
Seller rating 5 out of 5 stars
Condition: Wie Neu. Zustandsbeschreibung: leichte Lagerspuren, leicht bestoßen/minor shelfwear, slightly bumped. Edited by Vipin Kumar Kukkala and Sudeep Pasricha. With contributions by Wanli Chang, Nan Chen, Shuai Zhao, Xiaotian Dai et al. XV,789 Seiten, gebunden (Springer-Verlag 2023). Statt EUR 117,69. Gewicht: 137 g - Gebunden/Gebundene Ausgabe.
-
US$ 124.14
US$ 16.70 shipping
Ships from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: Brand New. 540 pages. 9.25x7.50x1.22 inches. In Stock.
-
Machine Learning for Indoor Localization and Navigation (Paperback)
Language: English
Published by Springer International Publishing AG, Cham, 2024
ISBN 10: 3031267141 ISBN 13: 9783031267147
Paperback. Condition: new. Paperback. While GPS is the de-facto solution for outdoor positioning with a clear sky view, there is no prevailing technology for GPS-deprived areas, including dense city centers, urban canyons, buildings and other covered structures, and subterranean facilities such as underground mines, where GPS signals are severely attenuated or totally blocked. As an alternative to GPS for the outdoors, indoor localization using machine learning is an emerging embedded and Internet of Things (IoT) application domain that is poised to reinvent the way we navigate in various indoor environments. This book discusses advances in the applications of machine learning that enable the localization and navigation of humans, robots, and vehicles in GPS-deficient environments. The book explores key challenges in the domain, such as mobile device resource limitations, device heterogeneity, environmental uncertainties, wireless signal variations, and security vulnerabilities. Countering these challenges can improve theaccuracy, reliability, predictability, and energy-efficiency of indoor localization and navigation. The book identifies severalnovel energy-efficient, real-time, and robust indoor localization techniques that utilize emerging deep machine learning and statistical techniques to address the challenges for indoor localization and navigation. In particular, the book:Provides comprehensive coverage of the application of machine learning to the domain of indoor localization;Presents techniques to adapt and optimize machine learning models for fast, energy-efficient indoor localization;Covers design and deployment of indoor localization frameworks on mobile, IoT, and embedded devices in real conditions. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
-
Machine Learning for Indoor Localization and Navigation
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 143.98
US$ 16.01 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
