赵静文 讲师，复旦大学理学博士
从事专业：计算机视觉
电话：13127516170 邮箱：jingwen_echo@outlook.com
研究方向
计算机视觉、生物医学影像分析
个人简介
赵静文，现为上海工程技术大学，bwin必赢，讲师。2013/09-2018/06就读于复旦大学，计算机科学技术学院，攻读计算机应用专业博士学位，2009/09-2013/06就读于华东理工大学，信息学院，攻读计算机科学与技术专业学士学位。
主要成果
一、代表性课题：
1. 上海市自然科学基金，17ZR1402300，用彩色深度相机三维跟踪人群和识别群体行为的若干关键问题的研究，2017.5.1-2020.4.30， 20万元，在研，参与
2. 国家自然科学基金面上项目，61175036， 群体三维运动的摄影测量与行为辨识方法的研究，2012.01-2015.12， 60万元，已结题，参与
二、代表性论文：
1.J. Zhao, H. Li, M. Duan, S. H. Wang, and Y. Q. Chen. Rapid identification of neuronal structures in electronic microscope image using novel combined multi-scale image features. NEUROCOMPUTING, 230.22 (2017.3): 152-159.
2. J. Zhao, S. H. Wang, X. Liu, Y. Liu, Y. Q. Chen, Early diagnosis of cirrhosis via automatic location and geometric description of liver capsule. The Visual Computer. December 2018, Volume 34, Issue 12, pp 1677–1689.
3. J. Zhao, G. Zhang, L. Tian, Y. Q. Chen, Real-time human detection with depth camera via a physical radius-depth detector and a CNN descriptor. 2017 IEEE International Conference on Multimedia and Expo (ICME 2017).
4. S. H. Wang, J. Zhao, and Y. Q. Chen, Robust Tracking of Fish Schools using CNN for Head Identification. Multimedia tools and applications, (2016): 1-19.
5. S. H. Wang, J. Zhao, X. Liu, Y. Liu, and Y. Q. Chen, 3D Tracking Swimming Fish School with Learned Kinematic Model using LSTM Network. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2017).
6. S. H. Wang, X. Liu, J. Zhao, J. L. Song, J. Q. Zhang, and Y. Q. Chen, Learning to Diagnose Cirrhosis via Combined Liver Capsule and Parenchyma Ultrasound Image Features. 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2016).
7. S. H. Wang, X. Liu, J. Zhao, Y. Liu, and Y. Q. Chen, 3D Tracking Swimming Fish School using a Master View Tracking First Strategy. 2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2016).
8. X. Liu, J. Song, J. Zhao, Y. Q. Chen, J. Zhang, Extracting and describing liver capsule contour in high-frequency ultrasound image for early hbv cirrhosis diagnosis. 2016 IEEE International Conference on Multimedia and Expo (ICME 2016).
9. X. Liu, J. Song, S. H. Wang, J. Zhao，Y. Q. Chen, Learning to diagnose cirrhosis with liver capsule guided ultrasound image classification. Sensors, 17.1 (2017): 149.
10. X. Liu, Z. Zhan, M. Yan, J. Zhao, Y. Q. Chen, Computer-aided Cirrhosis Diagnosis via Automatic Liver Capsule Extraction and Combined Geometry-texture Features. 2017 IEEE International Conference on Multimedia and Expo (ICME 2017).
11. L. Tian, M. Li, G. Zhang, J. Zhao, Robust Human Detection with Super-pixel Segmentation and Random Ferns Classification Using RGB-D Camera. 2017 IEEE International Conference on Multimedia and Expo (ICME 2017).
