3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / Shan Liu, Min Zhang, Pranav Kadam, C.-C. Jay Kuo.
Material type: TextLanguage: English Publication details: Cham : Springer International Publishing AG, 2021.Description: 1 online resource : illustrations (chiefly color)ISBN:- 9783030891800
- 3030891801
- 006.37 23 LIU
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.
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