3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / Shan Liu, Min Zhang, Pranav Kadam, C.-C. Jay Kuo.

By:

Contributor(s):

Material type: Text

TextLanguage: English Publication details: Cham : Springer International Publishing AG, 2021.Description: 1 online resource : illustrations (chiefly color)ISBN:

9783030891800
3030891801

Subject(s):

DDC classification:

006.37 23 LIU

Online resources:

Contents:

I. Introduction.- II. Traditional point cloud analysis.- III. Deep-learning-based point cloud analysis.- IV. Explainable machine learning methods for point cloud analysis.- V. Conclusion and future work.

Summary: The comparison and analysis between the three types of methods are given to help readers have a deeper understanding. With the rich deep learning literature in 2D vision, a natural inclination for 3D vision researchers is to develop deep learning methods for point cloud processing.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
General Books	CUTN Central Library Generalia	Non-fiction	006.37 LIU (Browse shelf(Opens below))	Available		49589

Includes bibliographical references and index.

I. Introduction.-
II. Traditional point cloud analysis.-
III. Deep-learning-based point cloud analysis.-
IV. Explainable machine learning methods for point cloud analysis.-
V. Conclusion and future work.

The comparison and analysis between the three types of methods are given to help readers have a deeper understanding. With the rich deep learning literature in 2D vision, a natural inclination for 3D vision researchers is to develop deep learning methods for point cloud processing.

There are no comments on this title.

to post a comment.