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Více informací o knize Deep Learning for 3D Vision: Algorithms and Applications

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Anotace knihy

3D deep learning is a rapidly evolving field that has the potential to transform various industries. This book provides a comprehensive overview of the current state-of-the-art in 3D deep learning, covering a wide range of research topics and applications. It collates the most recent research advances in 3D deep learning, including algorithms and applications, with a focus on efficient methods to tackle the key technical challenges in current 3D deep learning research and adoption, therefore making 3D deep learning more practical and feasible for real-world applications.

This book is organized into five sections, each of which addresses different aspects of 3D deep learning. Section I: Sample Efficient 3D Deep Learning, focuses on developing efficient algorithms to build accurate 3D models with limited annotated samples. Section II: Representation Efficient 3D Deep Learning, deals with the challenge of developing efficient representations for dynamic 3D scenes and multiple 3D modalities. Section III: Robust 3D Deep Learning, presents methods for improving the robustness and reliability of deep learning models in real-world applications. Section IV: Resource Efficient 3D Deep Learning, explores ways to reduce the computation cost of 3D models and improve their efficiency in resource-limited environments. Section V: Emerging 3D Deep Learning Applications, showcases how 3D deep learning is transforming industries and enabling new applications for healthcare and manufacturing.

This collection is a valuable resource for researchers and practitioners interested in exploring the potential of 3D deep learning.

Parametry knihy

Zařazení knihy Knihy v němčině Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Informatik

• Plný název: Deep Learning for 3D Vision: Algorithms and Applications
• Autor: Xulei Yang, Hao Su
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 500
• EAN: 9789811286483
• ISBN: 9811286485
• ID: 44583205
• Nakladatelství: WORLD SCIENTIFIC PUB CO INC
• Hmotnost: 824 g
• Datum vydání: 06. June 2024

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