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Cheng-Ju Hsieh

dblp:55/1981 · DBLP profile ↗
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5ranked-venue papers
1as first author
2since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 3Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-author · 2 since 2021Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Face, body and person analysis · 50% Generative modeling · 50%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Generative modeling
cycle-consistent generative modeling		 0.612022
Augmentation of rPPG Benchmark Datasets: Learning to Remove and Embed rPPG Signals via Double Cycle Consistent Learning from Unpaired Facial Videos · ECCV (16) 2022
Computer vision › Face, body and person analysis › face analysis
remote photoplethysmography		 0.612022
Augmentation of rPPG Benchmark Datasets: Learning to Remove and Embed rPPG Signals via Double Cycle Consistent Learning from Unpaired Facial Videos · ECCV (16) 2022

Methods — techniques the papers use, named apart from their topics

unpaired video translation · 0.6cycle consistency · 0.6
YearPublicationVenuePosition
2022 Domain Generalized RPPG Network: Disentangled Feature Learning with Domain Permutation and Domain Augmentation
Wei-Hao Chung, Cheng-Ju Hsieh, Sheng-Hung Liu, Chiou-Ting Hsu
 ACCV (2)2
2022 Augmentation of rPPG Benchmark Datasets: Learning to Remove and Embed rPPG Signals via Double Cycle Consistent Learning from Unpaired Facial Videos
Cheng-Ju Hsieh, Wei-Hao Chung, Chiou-Ting Hsu
 ECCV (16)1
2004 Intermittent Scan Chain Fault Diagnosis Based on Signal Probability Analysis
abstract
A new algorithm to diagnose intermittent scan chain fault in scan-based designs is proposed in this paper. An intermittent scan chain fault sometimes is triggered and sometimes is not triggered during scan chain shifting, which makes it very difficult to locate the fault sites. In this paper, we provide answers to three questions: (1) Why intermittent scan chain faults happen? (2) Why diagnosis of this type of faults is necessary? (3) How to diagnose this type of faults? The experimental results presented demonstrate that the proposed diagnosis algorithm is effective for large industrial designs with multiple intermittent scan chain faults.
Yu Huang 0005, Wu-Tung Cheng, Cheng-Ju Hsieh, Huan-Yung Tseng, Alou Huang, Yu-Ting Hung
 DATE3
2003 Efficient Diagnosis for Multiple Intermittent Scan Chain Hold-Time Faults
abstract
When VLSI design and process enter the stage of ultra deep submicron (UDSM), process variations, signal integrity (SI) and design integrity (DI) issues can no longer be ignored. These factors introduce some new problems in VLSI design, test and diagnosis, which increase lime-to-market, time-to-volume and cost for silicon debug. Intermittent scan chain hold-time fault is one of such problems we encountered in practice. The fault sites have to be located to speedup silicon debug and improve yield. Recent study of the problem proposed a statistical algorithm to diagnose the faulty scan chains if only one fault per chain. Based on the previous work, in this paper, an efficient diagnosis algorithm is proposed to diagnose faulty scan chains with multiple faults per chain. The presented experimental results on industrial designs show that the proposed algorithm achieves good diagnosis resolution in reasonable time.
Yu Huang 0005, Wu-Tung Cheng, Cheng-Ju Hsieh, Huan-Yung Tseng, Alou Huang, Yu-Ting Hung
 Asian Test Symposium3
2003 Statistical Diagnosis for Intermittent Scan Chain Hold-Time Fault
abstract
Intermittent scan chain hold-time fault is discussed in this paper and a method to diagnose the faulty site in a scan chain is proposed as well. Unlike the previous scan chain diagnosis methods that targeted permanent faults only, the proposed method targets both permanent faults and intermittent faults. Three ideas are presented in this paper. First an enhanced upper bound on the location of candidate faulty scan cells is obtained. Second a new method to determine a lower bound is proposed. Finally a statistical diagnosis algorithm is proposed to calculate the probabilities of the bounded set of candidate faulty scan cells. The proposed algorithm is shown to be efficient and effective for large industrial designs with multiple faulty scan chains. 1
Yu Huang 0005, Wu-Tung Cheng, Sudhakar M. Reddy, Cheng-Ju Hsieh, Yu-Ting Hung
 ITC4