國立虎尾科技大學 |

Deep learning for 3D vision = algorithms and applications /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Deep learning for 3D vision/ edited by Xiaoli Li, Xulei Yang, Hao Su.
Reminder of title:	algorithms and applications /
other author:	Li, Xiaoli.
Published:	Singapore :World Scientific, : c2024.,
Description:	1 online resource (xiii, 480 p.) :ill. :
Subject:	Three-dimensional imaging - Data processing. -
Online resource:	https://www.worldscientific.com/worldscibooks/10.1142/13683#t=toc
ISBN:	9789811286490

Deep learning for 3D vision = algorithms and applications /
Deep learning for 3D visionalgorithms and applications /[electronic resource] :edited by Xiaoli Li, Xulei Yang, Hao Su. - 1st ed. - Singapore :World Scientific,c2024. - 1 online resource (xiii, 480 p.) :ill.

Includes bibliographical references and index.

"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"-- Provided by publisher.

ISBN: 9789811286490Subjects--Topical Terms:

1497644
Three-dimensional imaging
--Data processing.

LC Class. No.: TA1560 / .D44 2024

Dewey Class. No.: 006.3/1

Deep learning for 3D vision = algorithms and applications /
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040 $a DLC $b eng $c DLC $d DLC
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050 0 0 $a TA1560 $b .D44 2024
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245 0 0 $a Deep learning for 3D vision $h [electronic resource] : $b algorithms and applications / $c edited by Xiaoli Li, Xulei Yang, Hao Su.
250 $a 1st ed.
260 $a Singapore : $b World Scientific, $c c2024.
300 $a 1 online resource (xiii, 480 p.) : $b ill.
504 $a Includes bibliographical references and index.
520 $a "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"-- Provided by publisher.
588 $a Description based on print version record.
650 0 $a Three-dimensional imaging $x Data processing. $3 1497644
650 0 $a Deep learning (Machine learning) $3 1381171
650 0 $a Computer vision. $3 561800
700 1 $a Li, Xiaoli. $3 1112228
700 1 $a Yang, Xulei. $3 1497642
700 1 $a Su, Hao. $3 1497643
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/13683#t=toc