杨晓梅
副教授
专业：自动化
方向：检测技术与装置、医学成像，电能质量数据智能分析，深度学习
email：yangxiaomei@scu.edu.cn
电话：028-85466818
期刊论文：
[1]. xiaomei. yang, lin yang, xianyong xiao and yang wang, "a novel detection method for supersynchronous resonance from synchrophasor data", ieee transactions on power systems, 2022, early access.
[2]. xiaomei yang, jianing zhang, xiaorong xie, xianyong xiao, bo gao, and yang wang*, " interpolated dft-based identification of sub-synchronous oscillation parameters using synchrophasor data", ieee transactions on smart grid, nov, 11(3): 2662-2675, 2020 .
[3]. xiaomei yang; yubo mei; xunyong hu; ruiseng luo; kai liu, “”, , vol. 29, pp. 21-25, 2022.
[4]. chen wang, xiaomei yang, shaomin fei, kai zhou , xiaofeng gong, miao du, ruisen luo, "scalar quantization as sparse least square optimization", ieee transactions on pattern analysis & machine intelligence, vol. 43, no. 5, may 2021：1678-1690.
[5]. xiaomei yang， lin yang， xianyong xiao， yang wang， shu zhang，“an adaptive lightweight seq2subseq model for non-intrusive load monitoring”, iet generation, transmission & distribution, 24 july 2022.
[6]. xiaomei yang, haoyi li, yubo mei, xunyong hu, yang wang, xianyong xiao,” application of adaptive chirp mode decomposition on parameter identification of sub/super-synchronous oscillation signals”, iet generation, transmission & distribution, 15 october 2021.
[7]. xiujuan zheng, chang zhang, hui chen, yun zhang, xiaomei yang*，“remote measurement of heart rate from facial video in different scenarios”，measurement 188, 110243, 2022
[8]. yang wang, hanlu yang, xiaorong xie, xiaomei yang* and guangrui chen, "real-time subsynchronous control interaction monitoring using improved intrinsic time-scale decomposition", journal of modern power systems and clean energy, 2022, early access.
[9]. yue ma, qi huang, haoy beng gooi, zhenyuan zhang, xiaomei yang and yang wang, "subsynchronous oscillation analysis using multisynchrosqueezing transform and dissipating energy flow method", ieee transactions on industry applications, vol. 58, no. 3, pp. 3134-3141, may-june 2022.
[10]. lin yang, linming guo, wenhai zhang and xiaomei yang*,” classification of multiple power quality disturbances by tunable-q wavelet transform with parameter selection”, energies, 2022, 15, 3428.
[11]. yue ma, dongsheng cai , xiaomei yang, qi huang. “a novel sso parameters identification technique for power grid with high proportion renewable energy using synchrophasor data”, international journal of electrical power and energy systems 132, 107131, 2021.
[12]. ;*;;;.””. ieee access, nov, 9(3): 35164-35177, 2021.
[13]. yang wang; xiaolong jiang; xiaorong xie; xiaomei yang; xianyong xiao，“”，, 36(5):3242-3254, 2021.
[14]. ying wang, hong lu, xianyong xiao, xiaomei yang, wenhai zhang, “”, , vol, 14(7): 1242 – 1250, 2020.
[15]. xiaomei yang，wen xu, ruisen luo, xiujuan zheng∗, and kai liu, " robustly reconstructing magnetic resonance images via structure decomposition", magnetic resonance imaging, 57, 165-175, 2019.
[16]. xiaomei yang, jiawei zhang, yanan liu, xiujuan zheng∗, and kai liu, "super-resolution image reconstruction using fractional-order total variation and adaptive regularization parameters", the visual computer, 35:1755–1768, 2019
[17]. kai liu, jianwen song, daniel l. lau, xiujuan zheng, ce zhu, and xiaomei yang*, " reconstructing 3d point clouds in real time with look-up tables for structured light scanning along both horizontal and vertical directions", optics letters, 44(25): 6029-6032,2019.
[18]. xiujuan zheng, zhanheng li, xinyi chun, xiaomei yang∗,and kai liu. " a model-based method with geometric solutions for gaze correction in eye-tracking", mathematical biosciences and engineering, 17(2):1396-1412, 2019.
[19]. jiaying deng, wenhai zhang, and xiaomei yang*, " recognition and classification of incipient cable failures based on variational mode decomposition and a convolutional neural network", energies 12, 2005,2019.
[20]. ning liu, bo fan, xianyong xiao, and xiaomei yang*, "cable incipient fault identification with a sparse autoencoder and a deep belief network", energies 12(18), 3424, 2019.
[21]. ruisen luo, qian feng, chen wang*, xiaomei yang, haiyan tu, qin yu, shaomin fei, and xiaofeng gong, "feature learning with a divergence-encouraging autoencoder for imbalanced data classification", ieee access, 2018, 6: 70197-70211
[22]. xiaomei yang, y. w. luo, s. j. chen, x. j. zhen, q. yu, k. liu∗, "dynamic mri reconstruction from highly undersampled (k, t)-space data using weighted schatten p-norm regularizer of tensor", magnetic resonance imaging, 37, 260-272, 2017.
[23]. y. inoue, xiaomei yang, m. nagao, , , etc. "peri-infarct dysfunction in post-myocardial infarction: assessment of 3-t tagged and late enhancement mri", , 20(5), 1139-1148, 2010.
[24]. kenya murase, s miyazaki and xiaomei yang, "an efficient method for calculating kinetic parameters in dual-input single-compartment model", british journal of radiology, 80(953), 371-375, 2007.
[25]. xiaomei yang, t. soma, kenya murase, "phase mutual information for mri and pet image registration: parameter selection of log-gabor filter"，japanese journal of medical physics, 27(3), 117-128, 2008.
[26]. k. yoshida, t. nagao, k. okada, s. miyazaki, xiaomei yang, y. yamazaki, k. murase. "development of a system for measuring wall shear stress in blood vessels using magnetic resonance imaging and computational fluid dynamics". japanese journal of medical physics, 27(3), 136-149, 2008.
[27]. kenya murase, w. mukai, s. fukami, k. matsumoto andxiaomei yang, "performance of model observers for lesion detection in spect imaging"，japanese journal of medical physics, 26(3),108-117, 2006
[28]. n. tanki, kenya murase, m. kumashiro, r. momoi, xiaomei yang, t. tabuchi, m. nagayama, and y. watanabe, "quantification of left ventricular volumes from cardiac cine mri using active contour model combined with gradient vector flow"，magnetic resonance in medical science. 4(4), 191-196, 2005