An Online Rapid Mesh Segmentation Method Based on an Online Sequential Extreme Learning Machine
The existing mesh segmentation methods currently require long training times and have high computational complexity. Consequently, many of these methods cannot meet the rapid requirements of digital geometry processing in the Web environment. This paper proposes an online rapid mesh segmentation met...
Main Authors: | Feiyu Zhao, Buyun Sheng, Xiyan Yin, Hui Wang, Xincheng Lu, Yuncheng Zhao |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8790697/ |
Similar Items
-
Online Sequential Extreme Learning Machine With Dynamic Forgetting Factor
by: Weipeng Cao, et al.
Published: (2019-01-01) -
Inverse-Matrix-Free Online Sequential Extreme Learning Machine
by: ZUO Pengyu, WANG Shitong
Published: (2020-01-01) -
Adaptive Online Sequential Extreme Learning Machine with Kernels for Online Ship Power Prediction
by: Xiuyan Peng, et al.
Published: (2021-08-01) -
Identity activation structural tolerance online sequential circular extreme learning machine for highlydimensional data
by: Sarutte Atsawaraungsu, et al.
Published: (2019-06-01) -
Sin Activation Structural Tolerance of Online Sequential Circular Extreme Learning Machine
by: Sarutte Atsawaraungsuk, et al.
Published: (2017-07-01)