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Published in Applied Intelligence 52 (14), 16246-16264, 2022
A model compression approach combining channel pruning with spatial attention knowledge distillation for efficient object detection.
Recommended citation: Y. Chu, P. Li, Y. Bai, Z. Hu, Y. Chen, J. Lu. (2022). "Group channel pruning and spatial attention distilling for object detection." Applied Intelligence. 52(14), 16246-16264.
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Published in 2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI), 2023
A hybrid spectrogram approach with group time-frequency attention for automatic respiratory sound classification.
Recommended citation: Y. Chu, Q. H. Wang, E. Z. Zhou, G. Zheng, Q. Liu. (2023). "Hybrid spectrogram for the automatic respiratory sound classification with group time frequency attention network." 2023 IEEE 6th International Conference on PRAI.
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Published in Complex & Intelligent Systems 11 (4), 200, 2025
An automatic respiratory sound classification framework combining improved deep clustering and contrastive learning.
Recommended citation: Y. Chu, Q. Wang, E. Zhou, L. Fu, Q. Liu, G. Zheng. (2025). "CycleGuardian: A framework for automatic respiratory sound classification based on improved deep clustering and contrastive learning." Complex & Intelligent Systems. 11(4), 200.
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Published in Biomedical Signal Processing and Control 112, 108491, 2026
EZhouNet leverages graph neural networks and anchor interval strategies for robust respiratory sound event detection.
Recommended citation: Y. Chu, Q. Wang, E. Zhou, Q. Liu, G. Zheng. (2026). "EZhouNet: A framework based on graph neural network and anchor interval for the respiratory sound event detection." Biomedical Signal Processing and Control. 112, 108491.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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