3D point cloud analysis : traditional, deep learning, and explainable machine learning methods /
Liu, Shan,
3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / Shan Liu, Min Zhang, Pranav Kadam, C.-C. Jay Kuo. - Cham : Springer International Publishing AG, 2021. - 1 online resource : illustrations (chiefly color)
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.
9783030891800 3030891801
Computer vision.
Pattern perception.
Machine learning.
006.37 / LIU
3D point cloud analysis : traditional, deep learning, and explainable machine learning methods / Shan Liu, Min Zhang, Pranav Kadam, C.-C. Jay Kuo. - Cham : Springer International Publishing AG, 2021. - 1 online resource : illustrations (chiefly color)
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.
9783030891800 3030891801
Computer vision.
Pattern perception.
Machine learning.
006.37 / LIU