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Wenming Yang

4 papers hereh-index 324 citations12 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI1
  • cs.CV1
  • cs.LG1
  • cs.RO1
same name
  • Wenming Yang — 6 papers, h 1
  • Wenming Yang — 5 papers, h 5
  • Wenming Yang — 4 papers, h 30
  • Wenming Yang — 2 papers, h 1
  • Wenming Yang — 2 papers, h 3
  • Wenming Yang — 2 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

cs.CV2026

OPD-IAD: From Language Judgment to Industrial Anomaly Detection via On-Policy Self-Distillation

Shuimu Chen, Jing Jin, Nan Su +5

Large vision-language models (LVLMs) have recently shown strong potential for industrial anomaly detection (IAD) by providing image-level anomaly judgments and interpretable defect…

cs.AI2026

CoRe-ECG: Advancing Self-Supervised Representation Learning for 12-Lead ECG via Contrastive and Reconstructive Synergy

Zehao Qin, Xiaojian Lin, Ping Zhang +6

Accurate interpretation of electrocardiogram (ECG) remains challenging due to the scarcity of labeled data and the high cost of expert annotation. Self-supervised learning (SSL) of…

cs.LG2025

VISTA: Unsupervised 2D Temporal Dependency Representations for Time Series Anomaly Detection

Sinchee Chin, Fan Zhang, Xiaochen Yang +5

Time Series Anomaly Detection (TSAD) is essential for uncovering rare and potentially harmful events in unlabeled time series data. Existing methods are highly dependent on clean,…

cs.RO2024

Rethinking 6-Dof Grasp Detection: A Flexible Framework for High-Quality Grasping

Pengwei Xie, Siang Chen, Wei Tang +3

Robotic grasping is a primitive skill for complex tasks and is fundamental to intelligence. For general 6-Dof grasping, most previous methods directly extract scene-level semantic…

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