Eye-redness grading system based on deep learning and smartphone images: Application and innovation of improved ConvNeXt model DOI

Xu Wang,

Tianlun Wang, Zuguo Liu

et al.

Published: Dec. 27, 2024

Language: Английский

An efficient transfer fault diagnosis method integrating feature redundancy selection and multi-strategy parameter optimization DOI
Wenchao Jia,

Aijun An,

Bin Gong

et al.

Expert Systems with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 127267 - 127267

Published: March 1, 2025

Language: Английский

Citations

0
An unsupervised multi-level fusion domain adaptation method for transfer diagnosis under time-varying working conditions DOI

Cuiying Lin,

Yun Kong, Qinkai Han

et al.

Mechanical Systems and Signal Processing, Journal Year: 2025, Volume and Issue: 228, P. 112458 - 112458

Published: Feb. 17, 2025

Language: Английский

Citations

0
TSSSKD-YOLO: an intelligent classification and defect detection method of insulators on transmission lines by fusing knowledge distillation in multiple scenarios DOI
Yongsheng Ye, Gary Tan, Qiang Liu

et al.

Multimedia Systems, Journal Year: 2025, Volume and Issue: 31(3)

Published: April 7, 2025

Language: Английский

Citations

0
A Lightweight Fault Diagnosis with Domain Adaptation for Defected Bearings DOI Creative Commons

Xiaohong Jiao,

Yongsheng Zhou,

Xuan Liu

et al.

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(8), P. 4579 - 4579

Published: April 21, 2025

This paper presents a lightweight fault diagnosis framework for bearing defects, integrating time-frequency analysis, deep learning, and model compression techniques to address challenges in resource-constrained environments. The proposed method combines the S-transform high-resolution representation with MobileNet as an efficient backbone network, enabling robust feature extraction from complex vibration signals. To enhance deployment on edge devices, knowledge distillation is employed compress model, significantly reducing computational complexity while maintaining diagnostic accuracy. Additionally, domain adaptation considered mitigate shift issues, ensuring performance across varying operating conditions. Experimental results demonstrate framework’s effectiveness, achieving high accuracy reduced overhead, making it practical solution real-time industrial applications. approach bridges gap between advanced learning requirements, offering scalable diagnosis.

Language: Английский

Citations

0
Eye-redness grading system based on deep learning and smartphone images: Application and innovation of improved ConvNeXt model DOI

Xu Wang,

Tianlun Wang, Zuguo Liu

et al.

Published: Dec. 27, 2024

Language: Английский

Citations

0