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以深度学习、迁移学习和元学习等人工智能技术为基础,探索声音和图像信号的底层特征描述、特征表示、分类决策等智能化信息处理关键理论。面向国防需求、工业应用等领域,研究设计目标检测、识别、跟踪,视觉测量以及声学异常及故障诊断的新方法、技术及系统。
- ,,,,,,,,,,,,,.Structure information preserving domain adaptation network for fault diagnosis of Sucker Rod Pumping systems:NEURAL NETWORKS,2025,188:-
- ,,,,,,.MC-GAT: multi-layer collaborative generative adversarial transformer for cholangiocarcinoma classification from hyperspectral pathological images:BIOMEDICAL OPTICS EXPRESS,2022,13:5794-5812
- ,,.类内-类间通道注意力少样本分类:光学精密工程,2023,31(21):3145-3155
- ,,.弱标签声音事件检测的空间-通道特征表征与自注意池化:电子学报,51(02):297-306
- ,,.A Task-Specific Meta-Learning Framework for Few-Shot Sound Event Detection:IEEE International Workshop on Multimedia Signal Processing,2022
- ,.Convolutional Receptive Field Dual Selection Mechanism for Acoustic Scene Classification:IEEE International Workshop on Multimedia Signal Processing,2021
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