collaborators

10 papers

eess.SP2026

CWT-Enhanced Vibration Sensing With Time-Frequency Region Localization Using YOLO

Po-Heng Chou, Wei-Lung Mao, Ru-Ping Lin +2

This letter presents a CWT-enhanced vibration sensing framework for bearing fault monitoring through localized time-frequency region detection on continuous wavelet transform (CWT)…

cs.NI2026

Measurement-Driven Early Warning of Reliability Breakdown in 5G NSA Railway Networks

Po-Heng Chou, Da-Chih Lin, Hung-Yu Wei +2

This paper presents a measurement-driven study of early warning for reliability breakdown events in 5G non-standalone (NSA) railway networks. Using 10~Hz metro-train measurement tr…

eess.SP2025

NGGAN: Noise Generation GAN Based on the Practical Measurement Dataset for Narrowband Powerline Communications

Ying-Ren Chien, Po-Heng Chou, You-Jie Peng +3

To effectively process impulse noise for narrowband powerline communications (NB-PLCs) transceivers, capturing comprehensive statistics of nonperiodic asynchronous impulsive noise…

cs.LG2025

MECKD: Deep Learning-Based Fall Detection in Multilayer Mobile Edge Computing With Knowledge Distillation

Wei-Lung Mao, Chun-Chi Wang, Po-Heng Chou +2

The rising aging population has increased the importance of fall detection (FD) systems as an assistive technology, where deep learning techniques are widely applied to enhance acc…

cs.CV2025

Automated Defect Detection for Mass-Produced Electronic Components Based on YOLO Object Detection Models

Wei-Lung Mao, Chun-Chi Wang, Po-Heng Chou +1

Since the defect detection of conventional industry components is time-consuming and labor-intensive, it leads to a significant burden on quality inspection personnel and makes it…

cs.CV2025

YOLO-Based Defect Detection for Metal Sheets

Po-Heng Chou, Chun-Chi Wang, Wei-Lung Mao

In this paper, we propose a YOLO-based deep learning (DL) model for automatic defect detection to solve the time-consuming and labor-intensive tasks in industrial manufacturing. In…