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厦门大学信息科学与技术学院智能科学与技术系导师介绍:苏松志

作者:聚创厦大考研网-小黑老师 点击量: 4232 发布时间: 2018-08-31 14:42 【微信号:13306030226】



  苏松志副教授
  厦门大学 博士(2011)
  研究方向: 计算机视觉、机器学习及其应用、人脸识别与行人检测、无人驾驶中的智能视觉技术、三维场景的感知与理解和航拍图片分析
  所属部门: 智能科学与技术系
  联系电话:
  +86-15980939316
  电子邮件:
  ssz (AT) xmu.edu.cn
  主讲课程:
  程序设计语言原理(本科生课程)
  机器学习(本科生课程)
  机器学习(硕博生课程)
  计算机视觉(博士生课程)
  在研项目:
  低空航拍下基于隐式姿态模型的平躺人体检测方法研究,青年科学基金项目,2013-2015
  代表性论文:
  苏松志*,李绍滋,蔡国榕.《行人检测:原理与应用》,厦大出版社-南强丛书,2016-3.
  Song-Zhi Su, Sin-Sian Wu, Shu-Yuan Chen, Der-Jhy Duh, and Shao-Zi Li, Multi-View Fall Detection Based on Spatio-Temporal Interest Points, Multimedia Tools and Applications, 2015, vol.74, no. 14, 15 July. DOI 10.1007/s11042-015-2766-3.
  Song-Zhi Su, Zhi-Hui Liu, Su-Ping Xu, Shao-Zi Li, Rongrong Ji. Depth image feature learning based on sparse auto-encoder for human detection, Signal Processing, 2015, 112:43-52. (SCI, JCR 3)
  Song-Zhi Su, Zong-Yu Lan, Shao-Zi Li, Shu-Yuan Chen, Category-specific scene categorization, Journal of the Chinese Institute of Engineers, 2015, 38(1):128-137. (SCI, JCR 4)
  Song-Zhi Su*, Shu-Yuan Chen. Analysis of feature fusion based on HIK SVM and its application for pedestrian detection. Abstract and Applied Analysis. 2013. (SCI)Volume 2013, page: 1-11, http://dx.doi.org/10.1155/2013/436062.
  Li-Chuan Geng, Pierre-Mar Jodoin , Song-Zhi Su*, Shao-Zi Li, CBDF: Compressed Binary Discriminative Feature, NeuroComputing, 2015, doi:10.1016/j.neucom.2015.07.120. (SCI, JCR 3区)
  Guo-Rong Cai, Pierre-Marc Jodoin, Shao-Zi Li, Yun-Dong Wu, Song-Zhi Su*, Zhen-Kun Huang. Perspective-SIFT: an efficient tool for low-altitude remote sensing image registration. Signal Processing, 2013. (SCI)
  Dao-Xun Xia, Song-Zhi Su*, Shao-Zi Li, Pierre-Mar Jodoin. Lying-Pose Detection with Training Dataset Expansion. ICIP, 2014.
  De-Dong Yuan, Jie Dong, Song-Zhi Su*, Shao-Zi Li, Rong-Rong Ji. Pursuing detector efficiency for simple scene pedestrian detection, The 20th Anniversary International Conference on MultiMedia Modeling Dublin, Ireland, 2014.
  Li-Chuang Geng, Song-Zhi Su, Dong-Lin Cao, Shao-Zi Li. Perspective-invariant image matching framework with binary feature descriptor and APSO. International Journal of Pattern Recognition and Artificial Intelligence, 2014, 28(8): 1-18. DOI: 10.1142/
  Si Chen, Shaozi Li, Song-Zhi Su, Donglin Cao, Rongrong Ji. Online Semi-supervised Compressive Coding for Robust Visual Tracking, Journal of Visual Communication and Image Representation, 2014,25:793-804.
  Si Chen, Shaozi Li, Songzhi Su, Qi Tian, Rongrong Ji. Online MIL tracking with instance-level semi-supervised learning, Neruocomputing, 2014,139:272-288.
  Hongbo Zhang, Shang-An Li, Shu-Yuan Chen, Song-Zhi Su, Der-Jyh Duh, and Shaozi Li, “Adaptive photograph retrieval method,” Multimedia Tools and Applications, vol. 70, no. 3, pp. 2189-2209, June, 2014. (SCI, EI)
  Bing Shuai, Cheng Yun, Shao-Zi Li, Song-Zhi Su. A hierarchical clustering based non-maximum suppression method in pedestrian detection. Intelligent Science and Intelligent Data Engineering. Springer Berlin Heidelberg, 2012. 201-209.
  Hong-Bo Zhang, Song-Zhi Su, Shao-Zi Li, Duan-Sheng Chen, Bineng Zhong, Rongrong Ji. Seeing actions through scene context. VCIP, 2013, 11.17-20.
  苏松志*, 李绍滋, 陈淑媛, 蔡国榕, 吴云东. 行人检测技术综述[J]. 电子学报. 2012, 40(4): 814-820. (EI)
  蔡国榕,*李绍滋,吴云东,苏松志,陈水利. 一种透视不变的图像匹配算法,自动化学报,2013, 39(7): 1053-1061.
  Zhang H, *Li S, Chen S, Su S, Lin X, Cao D, 2013. Locating and recognizing multiple human actions by searching for maximum-score subsequences, Signal, Image and Video Processing, DOI: 10.1007/s11760-013-0501-y.
  *Su S, Chen S, 2013. Analysis of feature fusion based on HIK SVM and its application for pedestrian detection, Abstract and Applied Analysis, 2013 (2013), Article ID: 436062.
  Zhang H, *Li S, Su S, Chen S, 2013. Selecting effective and discriminative spatio-temporal interest points for recognizing human action, IEICE Transactions on Information and Systems, E96-D(8): 1783-1792.
  Cai G, Pierre-Marc J, Li S, Wu Y, Su S, Huang Z, 2013. Perspective-SIFT: An efficient tool for low-altitude remote sensing image registration, Signal Processing, 93(11): 3088-3110.


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