Deep Learning For 3d Vision: Algorithms And Applications
Regular price
€179.80
14 days return policy
Shipping & Delivery
3D Computer Vision
3D Deep Learning
Age Group_Uncategorized
Age Group_Uncategorized
Artificial Intelligence
automatic-update
Autonomous Driving
B01=Hao Su
B01=Xiaoli Li
B01=Xulei Yang
Category1=Non-Fiction
Category=UYQM
Computation-efficient Learning
Computer Vision
COP=Singapore
Deep Learning
Delivery_Delivery within 10-20 working days
eq_bestseller
eq_computing
eq_isMigrated=0
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Language_English
Multi-modality Learning
PA=Available
Point Cloud Analysis
Price_€100 and above
PS=Active
Robot Perception
Robust Learning
Sample-efficient Learning
softlaunch
Product details
- ISBN 9789811286483
- Publication Date: 20 Sep 2024
- Publisher: World Scientific Publishing Co Pte Ltd
- Publication City/Country: SG
- Product Form: Hardback
- Language: English
Secure
checkout
Fast Shipping
Easy returns
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.
