General

​Associate Professor 


Research Areas

​deep learning and the application in weak label learning.


Education

Ph.D. in college of science china agricultural university, 2011

M.S. in college of science china agricultural university, 2006



Experience



Work Experience

2017-12-now, School of Economics and Management, University of Chinese Academy of Sciences, Assoicate Professor.

2013-05 -2017-11, School of Economics and Management, University of Chinese Academy of Sciences, Assistant Professor.

2011-07-2013-05 , School of Economics and Management, University of Chinese Academy of Sciences, Postdoctoral Researcher.


Teaching Experience
Deep learning and application, 2021, 2022,2023

Publications

   
Papers

[1] Shi, Yong, Yang, Jie, Qi, Zhiquan. Unsupervised anomaly segmentation via deep feature reconstruction. NEUROCOMPUTING[J]. 2021, 424: 9-22,

[2] Li, Biao, Shi, Yong, Wang, Bo, Qi, Zhiquan, Liu, Jiabin. RGSR: A two-step lossy JPG image super-resolution based on noise reduction. NEUROCOMPUTING[J]. 2021, 419: 322-334, http://dx.doi.org/10.1016/j.neucom.2020.08.056.

[3] Shi, Yong, Liu, Jiabin, Wang, Bo, Qi, Zhiquan, Tian, YingJie. Deep learning from label proportions with labeled samples. NEURAL NETWORKS[J]. 2020, 128: 73-81, http://dx.doi.org/10.1016/j.neunet.2020.04.026.

[4] Qi, Zhiquan, Tian, Yingjie, Shi, Yong, Alexandrov, Vassil. Parallel RMCLP Classification Algorithm and Its Application on the Medical Data. IEEE TRANSACTIONS ON CLOUD COMPUTING[J]. 2020, 8(2): 532-538, https://www.webofscience.com/wos/woscc/full-record/WOS:000542966000018.

[5] Meng, Fan, Qi, Zhiquan, Chen, Zhensong, Wang, Bo, Shi, Yong. Token based crack detection. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS[J]. 2020, 38(3): 3501-3513, [6] Li, Biao, Wang, Bo, Liu, Jiabin, Qi, Zhiquan, Shi, Yong. s-LWSR: Super Lightweight Super-Resolution Network. IEEE TRANSACTIONS ON IMAGE PROCESSING[J]. 2020, 29: 8368-8380, http://dx.doi.org/10.1109/TIP.2020.3014953.

[7] Shi, Yong, Li, Biao, Wang, Bo, Qi, Zhiquan, Liu, Jiabin. Unsupervised Single-Image Super-Resolution with Multi-Gram Loss. ELECTRONICS[J]. 2019, 8(8): https://doaj.org/article/2efb006ca59346c0b9e19a668b50cd6f.

[8] Zhang, Fan, Liu, Jiabin, Wang, Bo, Qi, Zhiquan, Shi, Yong. A Fast Algorithm for Multi-Class Learning from Label Proportions. ELECTRONICS[J]. 2019, 8(6): https://doaj.org/article/f5a9d6785c8c4ab7a62b7e2c2c63e17b.

http://lib.cqvip.com/Qikan/Article/Detail?id=90877168504849574854495049.

[9] Li Biao, Shi Yong, Li Sujuan, Wang Bo, Qi Zhiquan, Liu Jiabin, HerreraViedma E, Shi Y, Berg D, Tien J, Cabrerizo FJ, Li J. A Novel Texture Generation Super Resolution Model. 7TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2019): INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT BASED ON ARTIFICIAL INTELLIGENCEnull. 2019, 162: 924-931, http://dx.doi.org/10.1016/j.procs.2019.12.069.

[10] Liu, Jiabin, Wang, Bo, Qi, Zhiquan, Tian, Yingjie, Shi, Yong, Wallach, H, Larochelle, H, Beygelzimer, A, dAlcheBuc, F, Fox, E, Garnett, R. Learning from Label Proportions with Generative Adversarial Networks. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019)null. 2019, 32: [11] Qi, Zhiquan, Meng, Fan, Tian, Yingjie, Niu, Lingfeng, Shi, Yong, Zhang, Peng. Adaboost-LLP: A Boosting Method for Learning With Label Proportions. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS[J]. 2018, 29(8): 3548-3559, https://www.webofscience.com/wos/woscc/full-record/WOS:000439627700020.

[12] Shi, Yong, Liu, Jiabin, Qi, Zhiquan, Wang, Bo. Learning from label proportions on high-dimensional data. NEURAL NETWORKS[J]. 2018, 103: 9-18, http://dx.doi.org/10.1016/j.neunet.2018.03.004.

[13] Shi, Yong, Liu, Jiabin, Qi, Zhiquan, IEEE. Inverse Convolutional Neural Networks for Learning from Label Proportions. 2018 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2018)null. 2018, 643-646, http://dx.doi.org/10.1109/WI.2018.00-21.

[14] Li Biao, Shi Yong, Qi Zhiquan, Chen Zhensong, Tong H, Li Z, Zhu F, Yu J. A Survey on Semantic Segmentation. 2018 18TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW)null. 2018, 1233-1240,