Ferrography Wear Particles Image Recognition Based on Extreme Learning Machine
The morphology of wear particles reflects the complex properties of wear processes involved in particle formation. Typically, the morphology of wear particles is evaluated qualitatively based on microscopy observations. This procedure relies upon the experts’ knowledge and, thus, is not always objec...
Saved in:
Main Authors: | Qiong Li, Tingting Zhao, Lingchao Zhang, Wenhui Sun, Xi Zhao |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2017-01-01
|
Series: | Journal of Electrical and Computer Engineering |
Online Access: | http://dx.doi.org/10.1155/2017/3451358 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A New Transfer Learning Ensemble Model with New Training Methods for Gear Wear Particle Recognition
by: Chunhua Zhao, et al.
Published: (2022-01-01) -
Theory and Numerical Analysis of Extreme Learning Machine and Its Application for Different Degrees of Defect Recognition of Hoisting Wire Rope
by: Zhike Zhao, et al.
Published: (2018-01-01) -
An Intelligent Heuristic Manta-Ray Foraging Optimization and Adaptive Extreme Learning Machine for Hand Gesture Image Recognition
by: Seetharam Khetavath, et al.
Published: (2023-09-01) -
Color Face Recognition Based on Steerable Pyramid Transform and Extreme Learning Machines
by: Ayşegül Uçar
Published: (2014-01-01) -
Wheel/Rail Adhesion State Identification of Heavy-Haul Locomotive Based on Particle Swarm Optimization and Kernel Extreme Learning Machine
by: Jianhua Liu, et al.
Published: (2020-01-01)