个人简介：
宋艳，女，现为山东大学海洋研究院助理研究员，主要开展机器学习在海洋声呐数据处理、机械设备故障检测与诊断中的应用研究，目前发表SCI/EI论文10余篇。目前主持国家自然科学基金青年项目1项、中央高校科研业务费项目1项。
E-mail: ysong@sdu.edu.cn
Abstract:
Dr. Yan Song, Assistant Professor in Institute of Marine Science and Technology, Shandong University, China. Her research interests focus on marine sonar data processing and fault diagnosis based on machine learning. She has published 10+ papers now.

学习工作经历：
中国海洋大学博士（2018）
Experiences:
Ph.D., Ocean University of China (2018)

研究方向：
声呐图像分割；故障诊断
Research Interests:
Sonar image segmentation; fault diagnosis

代表性著作/Selected Publications：
[1] Song Y, He B*, Liu P. Real-time Object Detection for AUVs Using Self-Cascaded Convolutional Neural Networks [J]. IEEE Journal of Oceanic Engineering, 2020, in press.
[2] Song Y, Yibin Li*, Jia L, Qiu M. Retraining Strategy based Domain Adaption Network for Intelligent Fault Diagnosis [J]. IEEE Transactions on Industrial Informatics, 2020, in press.
[3] Song Y*, Liu P. Segmentation of sonar images with intensity inhomogeneity based on improved MRF [J]. Applied Acoustics, 2020, 158: 107051.
[4] Song Y, He B*, Liu P, et al. Side scan sonar image segmentation and synthesis based on extreme learning machine [J]. Applied Acoustics, 2019, 146: 56-65.
[5] Liu P, Song Y*. Segmentation of sonar imagery using convolutional neural networks and Markov random field [J]. Multidimensional Systems and Signal Processing, 2019: 1-27.
[6] He B*^#, Song Y^#, Zhu Y, et al. Local receptive fields based extreme learning machine with hybrid filter kernels for image classification[J]. Multidimensional systems and signal processing, 2019, 30(3): 1149-1169.
[7] Song Y, He B*, Zhao Y, et al. Segmentation of sidescan sonar imagery using markov random fields and extreme learning machine [J]. IEEE Journal of Oceanic Engineering, 2018, 44(2): 502-513.
[8] Song Y, Zhang S, He B*, et al. Gaussian derivative models and ensemble extreme learning machine for texture image classification [J]. Neurocomputing, 2018, 277: 53-64.
[9] Zhang H G, Wu L, Song Y, et al. An online sequential learning non-parametric value-at-risk model for high-dimensional time series [J]. Cognitive Computation, 2018, 10(2): 187-200.