EDBT 2026 Demo / reviewers in the wild / expert
Bing Zhou 0003
dblp:90/3394-3
· DBLP profile ↗
5ranked-venue papers in the field
0as first author
4since 2021 · last 2025
0000-0003-3446-3903ORCID · conflict
Domains — venue-derived; a paper can count in several
Knowledge Engineering, Semantic Web & Information Systems · 3Data Mining & Knowledge Discovery · 2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Rethinking Contrastive Learning for Electrocardiogram Anomaly Detection: A Time-Frequency Augmentations Perspective
Huihui Chang, Haoyi Fan, Mingzhe Han, Bing Zhou 0003, Zongmin Wang |
PAKDD (1) | 5 |
| 2023 | ECG-MAKE: An ECG signal delineation approach based on medical attribute knowledge extraction
Zhaoyang Ge, Huiqing Cheng, Zhuang Tong, Ning Wang 0037, Adi Alhudhaif, Fayadh Alenezi, Haiyan Wang 0021, Bing Zhou 0003, Zongmin Wang |
Inf. Sci. | 8 |
| 2022 | Unsupervised semantic-aware adaptive feature fusion network for arrhythmia detection
Panpan Feng, Zhaoyang Ge, Haiyan Wang 0021, Yanjie Zhou, Bing Zhou 0003, Zongmin Wang |
Inf. Sci. | 6 |
| 2021 | Interactive ECG annotation: An artificial intelligence method for smart ECG manipulation
Haiyan Wang 0021, Yanjie Zhou, Bing Zhou 0003, Xiangdong Niu, Zongmin Wang |
Inf. Sci. | 3 |
| 2019 | Traffic Simulation and Visual Verification in SmogabstractSmog causes low visibility on the road and it can impact the safety of traffic. Modeling traffic in smog will have a significant impact on realistic traffic simulations. Most existing traffic models assume that drivers have optimal vision in the simulations, making these simulations are not suitable for modeling smog weather conditions. In this article, we introduce the Smog Full Velocity Difference Model (SMOG-FVDM) for a realistic simulation of traffic in smog weather conditions. In this model, we present a stadia model for drivers in smog conditions. We introduce it into a car-following traffic model using both psychological force and body force concepts, and then we introduce the SMOG-FVDM. Considering that there are lots of parameters in the SMOG-FVDM, we design a visual verification system based on SMOG-FVDM to arrive at an adequate solution which can show visual simulation results under different road scenarios and different degrees of smog by reconciling the parameters. Experimental results show that our model can give a realistic and efficient traffic simulation of smog weather conditions. Mingliang Xu 0001, Shili Chu, Yong Gan, Xiaoheng Jiang, Bing Zhou 0003 |
ACM Trans. Intell. Syst. Technol. | 7 |