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Ruiyun Yu
Professor Supervisor of Doctorate Candidates Supervisor of Master's Candidates
Name (English):Ruiyun Yu
Name (Pinyin):Yu Ruiyun
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[1]B. Guo , Q. Zuo, R. Yu. Point Cloud Segmentation of Integrated Circuits Package Substrates Surface Defects Using Causal Inference: Dataset Construction and Methodology. AAAI Conference on Artificial Intelligence. 2026. (CCF A).
[2]R. Yu, Z. Zhao and S. Zhen. Auxiliary Information Flow for 3D Industrial Defect Detection on IC Ceramic Package Substrate Surfaces: Dataset and Benchmark. IEEE Transactions on Circuits and Systems for Video Technology, 2026. (中科院1区TOP).
[3]S. Cao, J. Li, R. Yu, et al. DWT-3DRec: DeepJSCC-based wireless transmission for efficient 3D scene reconstruction using CityNeRF. Digital Communications and Networks, 2025..
[4]R. Yu , M. Chen, B. Liu. A triple-phase boost transformer for industrial equipment fault prediction. Neurocomputing, 2025, 619: 129137..
[5]R. Yu, B. Guo, and H. Li. "Anomaly Detection of Integrated Circuits Package Substrates Using the Large Vision Model SAIC: Dataset Construction, Methodology, and Application," in IEEE/CVF International Conference on Computer Vision, 2025. (CCF A).
[6]S. Zhen, R. Yu and H. Li, "MEDNet: Memory-Enhanced Discriminative Feature Learning for Few-Shot Metal Defect Classification", in The 51th Annual Conference of the IEEE Industrial Electrics Society..
[7]A. Ibrahim, Q. Zhao, H. Li, and R. Yu, "Feature Adaptive Selection and Fusion Network for Small Object Detection in Traffic Perception", in The 51th Annual Conference of the IEEE Industrial Electrics Society..
[8]H. Li, R. Yu and B. Guo, "Fine-Grained Region Perception Network for Few-Shot Defect Classification of IC Package Substrates: Benchmark Methodology and Dataset", in The 51th Annual Conference of the IEEE Industrial Electrics Society..
[9]R. Yu, H. Li, B. Guo and Z. Zhao, "Background-Weaken Generalization Network for Few-Shot Industrial Metal Defect Segmentation," in IEEE Transactions on Instrumentation and Measurement, vol. 74, pp. 1-11, 2025. (IF:5.9, SCI JCR Q1).
[10]M. Chen, R. Yu, Z. Liang, K. Li, H. Qi, "A Multiscale Process-aware Retention Network for Fault Prediction in Mixed-model Production," Computers in Industry, vol. 170, 104313, 2025. (IF:9.1, 中科院1区).
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