Lingua: Inglese
Editore: Springer Nature Switzerland AG, Cham, 2025
ISBN 10: 9819634970 ISBN 13: 9789819634972
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Hardcover. Condizione: new. Hardcover. This book describes novel ways of using deep learning to solve real-world problems. It covers advanced deep learning topics like neural architecture search, ensemble deep learning, transfer learning techniques, lightweight architectures, hybrid deep learning approaches, and generative adversarial networks. The book discusses the use of these advanced topics in selected applications like image classification, object detection, image steganography, protein secondary structure prediction, and gene expression data classification. Various challenges and future research directions falling under the scope of these topics are discussed. This book describes novel ways of using deep learning to solve real-world problems. It covers advanced deep learning topics like neural architecture search, ensemble deep learning, transfer learning techniques, lightweight architectures, hybrid deep learning approaches, and generative adversarial networks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Lingua: Inglese
Editore: Springer, Springer Nature Singapore, 2025
ISBN 10: 9819634970 ISBN 13: 9789819634972
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes novel ways of using deep learning to solve real-world problems. It covers advanced deep learning topics like neural architecture search, ensemble deep learning, transfer learning techniques, lightweight architectures, hybrid deep learning approaches, and generative adversarial networks. The book discusses the use of these advanced topics in selected applications like image classification, object detection, image steganography, protein secondary structure prediction, and gene expression data classification. Various challenges and future research directions falling under the scope of these topics are discussed.
Lingua: Inglese
Editore: Springer-Nature New York Inc, 2025
ISBN 10: 9819634970 ISBN 13: 9789819634972
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Lingua: Inglese
Editore: Springer, Berlin, Springer Nature Singapore, Springer, 2025
ISBN 10: 9819634970 ISBN 13: 9789819634972
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes novel ways of using deep learning to solve real-world problems. It covers advanced deep learning topics like neural architecture search, ensemble deep learning, transfer learning techniques, lightweight architectures, hybrid deep learning approaches, and generative adversarial networks. The book discusses the use of these advanced topics in selected applications like image classification, object detection, image steganography, protein secondary structure prediction, and gene expression data classification. Various challenges and future research directions falling under the scope of these topics are discussed. 186 pp. Englisch.
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Aggiungi al carrelloBuch. Condizione: Neu. Advances in Deep Learning, Volume 2 | M. Arif Wani (u. a.) | Buch | Studies in Big Data | xvi | Englisch | 2025 | Springer | EAN 9789819634972 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Springer, Springer Mai 2025, 2025
ISBN 10: 9819634970 ISBN 13: 9789819634972
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Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book describes novel ways of using deep learning to solve real-world problems. It covers advanced deep learning topics like neural architecture search, ensemble deep learning, transfer learning techniques, lightweight architectures, hybrid deep learning approaches, and generative adversarial networks. The book discusses the use of these advanced topics in selected applications like image classification, object detection, image steganography, protein secondary structure prediction, and gene expression data classification. Various challenges and future research directions falling under the scope of these topics are discussed.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 204 pp. Englisch.
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