Adaptive convolutional neural network-based principal component analysis algorithm for the detection of manufacturing data
Herein, an adaptive convolutional neural network (CNN)-based principal component analysis (PCA) algorithm for the detection of manufacturing data is proposed. The mentioned algorithm adaptively selects a suitable classification scheme (a CNN-based scheme or PCA-based support vector machine scheme) o...
Saved in:
| Main Author: | Tsun-Kuo Lin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-04-01
|
| Series: | Advances in Mechanical Engineering |
| Online Access: | https://doi.org/10.1177/16878132251325420 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Adaptive dimensionality reduction for neural network-based online principal component analysis.
by: Nico Migenda, et al.
Published: (2021-01-01) -
Towards more efficient initialization methods for Convolutional Neural Networks via K-Means and Principal Components
by: Federico Rabinovich, et al.
Published: (2025-04-01) -
Novel adaptive generalized principal component analysis algorithm based on Hebbian rule
by: Yingbin GAO, et al.
Published: (2020-07-01) -
EXPERIMENTAL RESEARCH AND ANALYSIS OF INFLUENCE OF PRINCIPAL PARAMETERS CONVOLUTIONAL NEURAL NETWORKS ON THE QUALITY OF THEIR TRAINING
by: Roman Mikhaylovich Nemkov, et al.
Published: (2022-05-01) -
Multi-scale Logo detection algorithm based on convolutional neural network
by: Yuchao JIANG, et al.
Published: (2020-04-01)