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DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206755118 ISBN 13: 9786206755111
Condition: New.
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Compiler Design Techniques: COMPILERS
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6207450094 ISBN 13: 9786207450091
Condition: New.
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Computational Intelligence for Green Cloud Computing and Digital Waste Management
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 261.55
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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Computational Intelligence for Green Cloud Computing and Digital Waste Management
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
£ 261.54
£ 15 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New.
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Condition: As New. Unread book in perfect condition.
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Computational Intelligence for Green Cloud Computing and Digital Waste Management
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206755118 ISBN 13: 9786206755111
Condition: New. Print on Demand.
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DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING
Language: English
Published by LAP LAMBERT Academic Publishing Nov 2023, 2023
ISBN 10: 6206755118 ISBN 13: 9786206755111
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch.
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DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206755118 ISBN 13: 9786206755111
Condition: New. PRINT ON DEMAND.
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DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING
Language: English
Published by LAP Lambert Academic Publishing, 2023
ISBN 10: 6206755118 ISBN 13: 9786206755111
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Prior to 2010, different image extraction projects were treated in the field of image recognition by mixing handmade features, manually created image local features and machine learning techniques. However, additional learned in the classroom image recognit.
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DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING
Language: English
Published by LAP LAMBERT Academic Publishing Nov 2023, 2023
ISBN 10: 6206755118 ISBN 13: 9786206755111
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Prior to 2010, different image extraction projects were treated in the field of image recognition by mixing handmade features, manually created image local features and machine learning techniques. However, additional learned in the classroom image recognition methods have been presented since the year 2010. In general object recognition contests, deep learning-based image recognition strategies have beat earlier technologies by a big amount. In order to better understand how deep learning is used in the field of image identification, this conference will also discuss the latest progress in deep learning-based autonomous driving.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.
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DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206755118 ISBN 13: 9786206755111
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Prior to 2010, different image extraction projects were treated in the field of image recognition by mixing handmade features, manually created image local features and machine learning techniques. However, additional learned in the classroom image recognition methods have been presented since the year 2010. In general object recognition contests, deep learning-based image recognition strategies have beat earlier technologies by a big amount. In order to better understand how deep learning is used in the field of image identification, this conference will also discuss the latest progress in deep learning-based autonomous driving.
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DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING
Language: English
Published by LAP LAMBERT Academic Publishing, 2023
ISBN 10: 6206755118 ISBN 13: 9786206755111
Taschenbuch. Condition: Neu. DEEP LEARNING-BASED IMAGE RECOGNITION FOR AUTONOMOUS DRIVING | Ravi Kumar Poluru | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206755111 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.
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Compiler Design Techniques: COMPILERS
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6207450094 ISBN 13: 9786207450091
Condition: New. Print on Demand.
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Compiler Design Techniques
Language: English
Published by LAP Lambert Academic Publishing, 2024
ISBN 10: 6207450094 ISBN 13: 9786207450091
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This course describes the basic techniques for compiler construction and tools that can be used to perform syntax directed translation of a high-level programming language into an executable code. It will provide deeper insights into the more advanced seman.
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Compiler Design Techniques: COMPILERS
Language: English
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6207450094 ISBN 13: 9786207450091
Condition: New. PRINT ON DEMAND.
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Computational Intelligence for Green Cloud Computing and Digital Waste Management
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
£ 266.46
£ 6.76 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHRD. 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.
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HRD. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the digital age, the relentless growth of data centers and cloud computing has given rise to a pressing dilemma. The power consumption of these facilities is spiraling out of control, emitting massive amounts of carbon dioxide, and contributing to the ever-increasing threat of global warming. Studies show that data centers alone are responsible for nearly eighty million metric tons of CO2 emissions worldwide, and this figure is poised to skyrocket to a staggering 8000 TWh by 2030 unless we revolutionize our approach to computing resource management. The root of this problem lies in inefficient resource allocation within cloud environments, as service providers often over-provision computing resources to avoid Service Level Agreement (SLA) violations, leading to both underutilization of resources and a significant increase in energy consumption. Computational Intelligence for Green Cloud Computing and Digital Waste Management stands as a beacon of hope in the face of the environmental and technological challenges we face. It introduces the concept of green computing, dedicated to creating an eco-friendly computing environment. The book explores innovative, intelligent resource management methods that can significantly reduce the power consumption of data centers. From machine learning and deep learning solutions to green virtualization technologies, this comprehensive guide explores innovative approaches to address the pressing challenges of green computing. Whether you are an educator teaching about green computing, an environmentalist seeking sustainability solutions, an industry professional navigating the digital landscape, a resolute researcher, or simply someone intrigued by the intersection of technology and sustainability, this book offers an indispensable resource.
