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In den WarenkorbPaperback. Zustand: Brand New. 1st edition. 200 pages. 9.45x6.69x0.47 inches. In Stock.
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In den WarenkorbZustand: New. In.
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In den WarenkorbZustand: New. 2020. 1st Edition. Paperback. . . . . . Books ship from the US and Ireland.
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In den Warenkorbhardcover. Zustand: Very Good.
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In den WarenkorbPaperback. Zustand: Brand New. 215 pages. 10.00x7.00x10.00 inches. In Stock.
Verlag: World Scientific Publishing Co Pte Ltd, 2012
ISBN 10: 9814291099 ISBN 13: 9789814291095
Sprache: Englisch
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In den WarenkorbHRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.
Verlag: World Scientific Publishing Company, Incorporated, 2012
ISBN 10: 9814291099 ISBN 13: 9789814291095
Sprache: Englisch
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In den WarenkorbZustand: New. pp. xii + 372 Illus.
Verlag: De Gruyter, De Gruyter Apr 2020, 2020
ISBN 10: 3110595532 ISBN 13: 9783110595536
Sprache: Englisch
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Machine Learning and Visual Perception provides an up-to-date overview on the topic, including the PAC model, decision tree, Bayesian learning, support vector machines, AdaBoost, compressive sensing and so on.Both classic and novel algorithms are introduced in classifier design, face recognition, deep learning, time series recognition, image classification, and object detection.Walter de Gruyter GmbH, Genthiner Strasse 13, 10785 Berlin 152 pp. Englisch.
Verlag: De Gruyter, Mercury Learning And Information, 2020
ISBN 10: 3110595532 ISBN 13: 9783110595536
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine Learning and Visual Perception provides an up-to-date overview on the topic, including the PAC model, decision tree, Bayesian learning, support vector machines, AdaBoost, compressive sensing and so on.Both classic and novel algorithms are introduced in classifier design, face recognition, deep learning, time series recognition, image classification, and object detection.
EUR 62,55
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In den WarenkorbTaschenbuch. Zustand: Neu. Machine Learning and Visual Perception | Baochang Zhang (u. a.) | Taschenbuch | X | Englisch | 2020 | De Gruyter | EAN 9783110595536 | Verantwortliche Person für die EU: Walter de Gruyter GmbH, De Gruyter GmbH, Genthiner Str. 13, 10785 Berlin, productsafety[at]degruyterbrill[dot]com | Anbieter: preigu.
Verlag: World Scientific Publishing Company, 2012
ISBN 10: 9814291099 ISBN 13: 9789814291095
Sprache: Englisch
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EUR 129,52
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In den WarenkorbZustand: New. In.
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In den WarenkorbZustand: New. In.
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In den WarenkorbZustand: New. In.
Verlag: World Scientific Pub Co Inc, 2012
ISBN 10: 9814291099 ISBN 13: 9789814291095
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 372 pages. 9.50x6.75x0.75 inches. In Stock.
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In den WarenkorbHardcover. Zustand: Brand New. 248 pages. 10.00x7.00x0.75 inches. In Stock.
Verlag: Springer Nature Singapore, Springer Nature Singapore Feb 2025, 2025
ISBN 10: 9819950708 ISBN 13: 9789819950706
Sprache: Englisch
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EUR 171,19
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In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -Deep learning has achieved impressive results in image classification, computer vision and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resources. The number of floating-point operations (FLOPs) has increased dramatically with larger networks, and this has become an obstacle for convolutional neural networks (CNNs) being developed for mobile and embedded devices. In this context, our book will focus on CNN compression and acceleration, which are important for the research community. We will describe numerous methods, including parameter quantization, network pruning, low-rank decomposition and knowledge distillation. More recently, to reduce the burden of handcrafted architecture design, neural architecture search (NAS) has been used to automatically build neural networks by searching over a vast architecture space. Our book will also introduce NAS due to its superiority and state-of-the-art performance in various applications, such as image classification and object detection. We also describe extensive applications of compressed deep models on image classification, speech recognition, object detection and tracking. These topics can help researchers better understand the usefulness and the potential of network compression on practical applications. Moreover, interested readers should have basic knowledge about machine learning and deep learning to better understand the methods described in this book.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 272 pp. Englisch.
Verlag: Springer Nature Singapore, Springer Nature Singapore Feb 2024, 2024
ISBN 10: 9819950678 ISBN 13: 9789819950676
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 171,19
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In den WarenkorbBuch. Zustand: Neu. Neuware -Deep learning has achieved impressive results in image classification, computer vision and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resources. The number of floating-point operations (FLOPs) has increased dramatically with larger networks, and this has become an obstacle for convolutional neural networks (CNNs) being developed for mobile and embedded devices. In this context, our book will focus on CNN compression and acceleration, which are important for the research community. We will describe numerous methods, including parameter quantization, network pruning, low-rank decomposition and knowledge distillation. More recently, to reduce the burden of handcrafted architecture design, neural architecture search (NAS) has been used to automatically build neural networks by searching over a vast architecture space. Our book will also introduce NAS due to its superiority and state-of-the-art performance in various applications, such as image classification and object detection. We also describe extensive applications of compressed deep models on image classification, speech recognition, object detection and tracking. These topics can help researchers better understand the usefulness and the potential of network compression on practical applications. Moreover, interested readers should have basic knowledge about machine learning and deep learning to better understand the methods described in this book.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 272 pp. Englisch.
Verlag: Springer Nature Singapore, Springer Nature Singapore, 2025
ISBN 10: 9819950708 ISBN 13: 9789819950706
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 175,77
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Deep learning has achieved impressive results in image classification, computer vision and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resources. The number of floating-point operations (FLOPs) has increased dramatically with larger networks, and this has become an obstacle for convolutional neural networks (CNNs) being developed for mobile and embedded devices. In this context, our book will focus on CNN compression and acceleration, which are important for the research community. We will describe numerous methods, including parameter quantization, network pruning, low-rank decomposition and knowledge distillation. More recently, to reduce the burden of handcrafted architecture design, neural architecture search (NAS) has been used to automatically build neural networks by searching over a vast architecture space. Our book will also introduce NAS due to its superiority and state-of-the-art performance in various applications, such as image classification and object detection. We also describe extensive applications of compressed deep models on image classification, speech recognition, object detection and tracking. These topics can help researchers better understand the usefulness and the potential of network compression on practical applications. Moreover, interested readers should have basic knowledge about machine learning and deep learning to better understand the methods described in this book.
Verlag: Springer Nature Singapore, Springer Nature Singapore, 2024
ISBN 10: 9819950678 ISBN 13: 9789819950676
Sprache: Englisch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
EUR 175,09
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In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Deep learning has achieved impressive results in image classification, computer vision and natural language processing. To achieve better performance, deeper and wider networks have been designed, which increase the demand for computational resources. The number of floating-point operations (FLOPs) has increased dramatically with larger networks, and this has become an obstacle for convolutional neural networks (CNNs) being developed for mobile and embedded devices. In this context, our book will focus on CNN compression and acceleration, which are important for the research community. We will describe numerous methods, including parameter quantization, network pruning, low-rank decomposition and knowledge distillation. More recently, to reduce the burden of handcrafted architecture design, neural architecture search (NAS) has been used to automatically build neural networks by searching over a vast architecture space. Our book will also introduce NAS due to its superiority and state-of-the-art performance in various applications, such as image classification and object detection. We also describe extensive applications of compressed deep models on image classification, speech recognition, object detection and tracking. These topics can help researchers better understand the usefulness and the potential of network compression on practical applications. Moreover, interested readers should have basic knowledge about machine learning and deep learning to better understand the methods described in this book.
Verlag: Springer-Nature New York Inc, 2024
ISBN 10: 9819950678 ISBN 13: 9789819950676
Sprache: Englisch
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 247,25
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In den WarenkorbHardcover. Zustand: Brand New. 269 pages. 9.25x6.10x9.21 inches. In Stock.