This book provides a comprehensive introduction on applying deep learning to the visual recognition of objects, bridging the gap between theoretical algorithms and high-impact practical implementations. Within these pages, readers will find a detailed exploration of advanced techniques for image restoration—including UNet-based defogging, feature fusion GANs, and ESRGAN super-resolution—alongside high-performance detection models. Specialized applications such as underwater crack segmentation using transfer learning, marine biological detection, and real-time analysis through YOLOv4, RetinaNet, and LSTM-integrated networks are also covered to provide researchers and engineers with a technical blueprint for solving diverse real-world computer vision challenges. Additionally, this work is also suitable as a textbook for advanced undergraduate and graduate students majoring in Artificial Intelligence, Intelligent Science and Technology, Computer Science, and Automation.
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Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Hardcover. Zustand: new. Hardcover. This book provides a comprehensive introduction on applying deep learning to the visual recognition of objects, bridging the gap between theoretical algorithms and high-impact practical implementations. Within these pages, readers will find a detailed exploration of advanced techniques for image restorationincluding UNet-based defogging, feature fusion GANs, and ESRGAN super-resolutionalongside high-performance detection models. Specialized applications such as underwater crack segmentation using transfer learning, marine biological detection, and real-time analysis through YOLOv4, RetinaNet, and LSTM-integrated networks are also covered to provide researchers and engineers with a technical blueprint for solving diverse real-world computer vision challenges. Additionally, this work is also suitable as a textbook for advanced undergraduate and graduate students majoring in Artificial Intelligence, Intelligent Science and Technology, Computer Science, and Automation. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9789819833344
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Zustand: New. Bestandsnummer des Verkäufers I-9789819833344
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Hardcover. Zustand: Brand New. 258 pages. 6.24x0.80x9.24 inches. In Stock. Bestandsnummer des Verkäufers x-9819833345
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Hardcover. Zustand: new. Hardcover. This book provides a comprehensive introduction on applying deep learning to the visual recognition of objects, bridging the gap between theoretical algorithms and high-impact practical implementations. Within these pages, readers will find a detailed exploration of advanced techniques for image restorationincluding UNet-based defogging, feature fusion GANs, and ESRGAN super-resolutionalongside high-performance detection models. Specialized applications such as underwater crack segmentation using transfer learning, marine biological detection, and real-time analysis through YOLOv4, RetinaNet, and LSTM-integrated networks are also covered to provide researchers and engineers with a technical blueprint for solving diverse real-world computer vision challenges. Additionally, this work is also suitable as a textbook for advanced undergraduate and graduate students majoring in Artificial Intelligence, Intelligent Science and Technology, Computer Science, and Automation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9789819833344
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Anbieter: AussieBookSeller, Truganina, VIC, Australien
Hardcover. Zustand: new. Hardcover. This book provides a comprehensive introduction on applying deep learning to the visual recognition of objects, bridging the gap between theoretical algorithms and high-impact practical implementations. Within these pages, readers will find a detailed exploration of advanced techniques for image restorationincluding UNet-based defogging, feature fusion GANs, and ESRGAN super-resolutionalongside high-performance detection models. Specialized applications such as underwater crack segmentation using transfer learning, marine biological detection, and real-time analysis through YOLOv4, RetinaNet, and LSTM-integrated networks are also covered to provide researchers and engineers with a technical blueprint for solving diverse real-world computer vision challenges. Additionally, this work is also suitable as a textbook for advanced undergraduate and graduate students majoring in Artificial Intelligence, Intelligent Science and Technology, Computer Science, and Automation. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Bestandsnummer des Verkäufers 9789819833344
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - This book provides a comprehensive introduction on applying deep learning to the visual recognition of objects, bridging the gap between theoretical algorithms and high-impact practical implementations. Within these pages, readers will find a detailed exploration of advanced techniques for image restoration-including UNet-based defogging, feature fusion GANs, and ESRGAN super-resolution-alongside high-performance detection models. Specialized applications such as underwater crack segmentation using transfer learning, marine biological detection, and real-time analysis through YOLOv4, RetinaNet, and LSTM-integrated networks are also covered to provide researchers and engineers with a technical blueprint for solving diverse real-world computer vision challenges. Additionally, this work is also suitable as a textbook for advanced undergraduate and graduate students majoring in Artificial Intelligence, Intelligent Science and Technology, Computer Science, and Automation. Bestandsnummer des Verkäufers 9789819833344
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