DEEP LEARNING FOR 3D VISION: ALGORITHMS AND APPLICATIONS - Rilegato

Li Xiaoli

Rilegato

ISBN 10: 9811286485 ISBN 13: 9789811286483

Casa editrice: World Scientific, 2024

Riassunto

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.

Dettagli dell'edizione

• Editore: World Scientific
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 9811286485
• ISBN 13: 9789811286483
• Rilegatura: Copertina rigida
• Numero di pagine: 494
• Contatto del produttore: World Scientific Publishing; https://www.worldscientific.com/; ; 5 Toh Tuck Link; #01-01; 596224; Singapore
• Persona responsabile: non disponibile