12 citations · 25 across the 9 of their papers we have counts for
9 papers
MAOL: Morphology-Aware Ordinal Learning for Fine-Grained Industrial Defect Severity Grading
Zhaoyang Wang, Haiyong Chen, Binyi Su +4
Fine-grained defect severity grading is essential for industrial inspection, yet remains challenging due to the ordinal nature of severity labels, the strong dependence on morpholo…
FuDU: A Fuzzy Dual-dimensional Uncertainty Framework for Streaming Active Learning in Industrial Defect Detection
Zhaoyang Wang, Haiyong Chen, Binyi Su +1
Ensuring the reliability of deep learning models in real-time industrial defect detection is critical for high-stakes quality inspection. To mine uncertain samples within continuou…
ICME 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for High-Precision Manufacturing
Wei Sun, Weixia Zhang, Linhan Cao +30
This paper presents the IEEE International Conference on Multimedia and Expo (ICME) 2026 Grand Challenge on Cross-Scenario Defect Detection and Fine-Grained Severity Grading for Hi…
OOVDet: Low-Density Prior Learning for Zero-Shot Out-of-Vocabulary Object Detection
Binyi Su, Chenghao Huang, Haiyong Chen
Zero-shot out-of-vocabulary detection (ZS-OOVD) aims to accurately recognize objects of in-vocabulary (IV) categories provided at zero-shot inference, while simultaneously rejectin…
Photovoltaic Defect Image Generator with Boundary Alignment Smoothing Constraint for Domain Shift Mitigation
Dongying Li, Binyi Su, Hua Zhang +2
Accurate defect detection of photovoltaic (PV) cells is critical for ensuring quality and efficiency in intelligent PV manufacturing systems. However, the scarcity of rich defect d…
Boosting Few-Shot Open-Set Object Detection via Prompt Learning and Robust Decision Boundary
Zhaowei Wu, Binyi Su, Qichuan Geng +2
Few-shot Open-set Object Detection (FOOD) poses a challenge in many open-world scenarios. It aims to train an open-set detector to detect known objects while rejecting unknowns wit…