Deep Learning For 3d Vision: Algorithms And Applications

Deep Learning For 3d Vision: Algorithms And Applications
Author :
Publisher : World Scientific
Total Pages : 493
Release :
ISBN-10 : 9789811286506
ISBN-13 : 9811286507
Rating : 4/5 (507 Downloads)

Book Synopsis Deep Learning For 3d Vision: Algorithms And Applications by : Xiaoli Li

Download or read book Deep Learning For 3d Vision: Algorithms And Applications written by Xiaoli Li and published by World Scientific. This book was released on 2024-08-27 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


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