出生灭顶灾，幸存苦海沤。
颤手握棋子，辛苦练三秋
沙袋绑下身，仍然晃悠悠
淮安到南京，上海到广州。
慢慢求医路，苦苦命几休。
磨难世罕见，天道勤相酬。
身残立，勇攀上层楼。
电大无门槛，自考争一流。
国赛露才智，软件显身手。
副相亲接见，勉助暖心头。
只手难写字，读到博士后。
双腿不能站，讲学到美欧。
口齿话不清，英语竟通透。
论文发要刊，吴奖何优秀。
就职中科院，频频新成就。
英伦诞霍金，甦菁出淮州
啧啧四海敬，奥运红旗手
简注：
1、手不能握物，用象棋子让他捏握，练了三年。
2、不能走路，无坐稳，用沙袋绑在腿上。
3、幼时到处求医，做手术，吃药，受尽了折磨。
4、高中毕业，成绩达线，因残疾无高校录取。

王甦菁发表的部分学术论文

1. Wang Su-Jing,Lin Bo, Wang Yong, Yi Tongqiang, Zou Bochao, Lyu Xiang-wen. Action Units recognition based on Deep Spatial-Convolutional and Multi-label Residual network [J]. Neurocomputing, 2019, 359: 130-138.
2. See John, Yap Moi Hoon, Li Jingting, Hong Xiaopeng,Wang Su-Jing. MEGC 2019 – The Second cial Micro-ssions Grand Challenge [C]. Proceedings of the 14th IEEE International Conference on Automatic ce & Gesture Recognition FG 2019, 2019, 1-5.
3. Li J., Soladié C., Séguier R.,Wang S., Yap M. H. Spotting Micro-ssions on Long Videos Sequences [C]. Proceedings of the 2019 14th IEEE International Conference on Automatic ce & Gesture Recognition FG 2019, 2019, 1-5.
4. Huang Xiaohua,Wang Su-Jng, Liu Xin, Zhao Guoying, Feng Xiaoyi, Pietikainen Matti. Discriminative Spatiotemporal Local Binary Pattern with Revisited Integral Projection for Spontaneous cial Micro-ssion Recognition [J]. IEEE Transactions on Affective Computing, 2019, 101: 32-47.
5. He Ying, Yang Han-Bo,Wang Su-Jing. CDBV: A Driving Dataset with Chinese Characteristics From a Bike View [J]. IEEE Access, 2019, 7: 51714-51723.
6. Su-Jing Wang, Bing-Jun Li, Yong-Jin Liu, Wen-Jing Yan, Xinyu Ou, Xiaohua Huang, Feng Xu, Xiaolan Fu. Micro-ssion Recognition with all Sample Size by Transferring Long-term Convolutional Neural Network [J]. Neurocomputing, 2018, 3120: 251-226.
7. ngbing Qu,Su-Jing Wang, Wen-Jing Yan, He Li, Shuhang Wu, Xiaolan Fu. CAE^2: A Database for Spontaneous Macro-ssion and Micro-ssion Spotting and Recognition [J]. IEEE Transactions on Affective Computing, 2018, 94: 424-436.
8. Mingyue Niu, Ya Li, Jianhua Tao,Su-Jng Wang. Micro-ssion Recognition Based on Local Two-Order Gradient Pattern [C]. Proceedings of the First Asian Conference on Affective Computing and Intelligent Interaction ACII Asia, 2018, 1-6.
9. Moi Hoon Yap, John See, Xiaopeng Hong, Su-Jing Wang. cial Micro-ssions Grand Challenge 2018 Summary [C]. Proceedings of the 2018 13th IEEE International Conference on Automatic ce & Gesture Recognition FG 2018, 2018, 675-678.
10. Wang, S-J.*, Wu S., Qian X., Li J., Fu X. A Main Directional Maximal Difference ysis for Spotting cial Movements from Long-term Videos[J]. Neurocomputing, 2017, 230382-389.
11. Wang, S-J.*, Yan, W-J., Sun, T., Zhao, G., & Fu, X. 2016. Sparse tensor canonical correlation ysis for micro-ssion recognition. Neurocomputing, 214, 218-232.
12. Wang, S-J., Wu S, Fu X. A Main Directional Maximal Difference ysis for Spotting Micro-ssions[C]. In Workshop on cial Informatics WFI, in conjunction with the Asian Conference on Computer Vision ACCV 2016, Taipei, November 20-24, 2016.
13. Liu, Y.-J., Zhang, J.-K., Yan, W.-J.,Wang, S.-J.*, Zhao, G., & Fu, X. L. 2016. A Main Directional Mean Optical Flow Feature for Spontaneous Micro-ssion Recognition. IEEE Transactions on Affective Computing, 74, 299-310.
14. 14.Chen, H.-L., Wang, G., Ma, C., Cai, Z.-N., Liu, W.-B., &Wang, S.-J.*2016. An Efficient Hybrid Kernel Extreme Learning Machine Approach for Early Diagnosis of Parkinsons Disease. Neurocomputing.184, 131-144.
15. Qu, F.,Wang, S.-J., Yan, W., & Fu, X.* 2016. CAE2: A Database of Spontaneous Macro-ssions and Micro-ssions. in Human-Computer Interaction. Novel User Experiences: 18th International Conference, HCI International 2016, Toronto, ON, Canada, July 17-22, 2016. Proceedings, Part III, M. Kurosu, Editor. 2016, Springer International Publishing: Cham. p. 48-59.
16. Yu, M., Liu, Y.-J.*,Wang, S.-J., Fu, Q., & Fu, X. 2016. A PMJ-inspired cognitive framework for natural scene categorization in line drawings. Neurocomputing, 173, Part 3, 2041-2048.
17. Huang, X.,Wang, S.-J., Zhao, G., & Piteikainen, M. . cial Micro-ssion Recognition Using Spatiotemporal Local Binary Pattern with Integral Projection. Paper presented at the Computer Vision Workshop ICCVW, IEEE International Conference on,, 1-9.
18. Wang, S.-J.*, Yan, W.-J., Li, X., Zhao, G., Zhou, C.-G., Fu, X., Yang, M., & Tao, J. . Micro-ssion Recognition Using Color Spaces. IEEE Transactions on Image Processing, 2412, 6034-6047.
19. Chen, H. l., Yang, B.,Wang, S.-J., Wang, G., Liu, D. y., Li, H. z., & Liu, W. b. 2014. Towards an optimal support vector machine classifier using a parallel particle swarm optimization strategy. Applied Mathematics and Computation, 2390, 180-197. doi: http://dx.doi.org/10.1016/j.amc.2014.04.039
20. Wang, S.-J., Yan, S., Yang, J., Zhou, C.-G., & Fu, X. 2014. A General Exponential Framework for Dimensionality Reduction. IEEE Transactions on Image Processing, 232, 920-930. doi: 10.1109/TIP.2013.2297020
21. Wang, S.-J., Chen, H.-L., Yan, W.-J., Chen, Y.-H., & Fu, X. 2014. ce Recognition and Micro-ssion Recognition Based on Discriminant Tensor Subspace ysis Plus Extreme Learning Machine. Neural Processing Letters, 391, 25-43. doi: 10.1007/s11063-013-9288-7
22. Wang, S.-J., Yan, W.-J., Li, X., Zhao, G., & Fu, X. L. 2014. Micro-ssion Recognition Using Dynamic Textures on Tensor Independent Color Space. Paper presented at the the 22nd International Conference on Pattern Recognition ICPR, Stockholm, Sweden.
23. Wang, S.-J., Yan, W.-J., Zhao, G., Fu, X., & Zhou, C.-G. 2014. Micro-ssion Recognition using Robust Principal Component ysis and Local Spatiotemporal Directional Features. Paper presented at the ECCV workshop on Spontaneous cial Behavior ysis.
24. Yan, W.-J.,Wang, S.-J., Chen, Y.-H., Zhao, G., & Fu, X. 2014. Quantifying Micro-ssions with Constraint Local Model and Local Binary Pattern. Paper presented at the ECCV workshop on Spontaneous cial Behavior ysis.
25. Yan, W.-J.,Wang, S.-J., Liu, Y.-J., Wu, Q., & Fu, X. 2014. For micro-ssion recognition: Database and suggestions. Neurocomputing, 1360, 82-87. doi: http://dx.doi.org/10.1016/j.neucom.2014.01.029
26. Yan, W.-J., Li, X.,Wang, S.-J., Zhao, G., Liu, Y.-J., Chen, Y.-H., & Fu, X. 2014. CAE II: An Improved Spontaneous Micro-ssion Database and the Baseline Evaluation. Plos one, 91, e86041. doi: 10.1371/journal.pone.0086041
27. Chen, H.-L., Huang, C.-C., Yu, X.-G., Xu, X., Sun, X., Wang, G., &Wang, S.-J. 2013. An efficient diagnosis system for detection of Parkinsons disease using fuzzy k-nearest nei**or approach.Expert Systems with Applications, 401, 263-271. doi: 10.1016/j.eswa.2012.07.014
28. Wang, S.-J., Zhou, C.-G., & Fu, X. 2013. Fusion Tensor Subspace Transformation Framework. Plos one, 87, e66647. doi: 10.1371/journal.pone.0066647
29. Yan, W.-J., Wu, Q., Liu, Y.-J.,Wang, S.-J., & Fu, X. 2013. CAE Database: A Dataset of Spontaneous Micro-ssions Collected From Neutralized ces. Paper presented at the the 10th IEEE Conference on Automatic ce and Gesture Recognition FG, Shanghai, China.
30. 梁静, 颜文靖, 吴奇, 申寻兵,王苏菁, & 傅小兰. 2013. 微表情研究的进展与展望. 中国科学基金, 272, 75-78.
31. Chen, H.-L., Yang, B., Wang, G.,Wang, S.-J., Liu, J., & Liu, D.-Y. 2012. Support Vector Machine Based Diagnostic System for Breast Cancer Using Swarm Intelligence. Journal of Medical Systems, 364, 2505-2519. doi: 10.1007/s10916-011-9723-0
32. Jia, C.-C.,Wang, S.-J., Peng, X.-J., Pang, W., Zhang, C.-Y., Zhou, C.-G., & Yu, Z.-Z. 2012. Incremental multi-linear discriminant ysis using canonical correlations for action recognition. Neurocomputing, 8316, 56-63.
33. Pang, E.-P.,Wang, S.-J., Qu, M.-Z., Liu, R., Jia, C.-C., & Yu, Z.-Z. 2012. 2D-SPP: A Two-dimensional Extension of Sparsity Preserving Projections. Journal of Information and Computational Science, 913, 3683-3692.
34. Wang, S.-J., Sun, M.-F., Chen, Y.-H., Pang, E.-P., & Zhou, C.-G. 2012. STPCA: Sparse Tensor Principal Component ysis for Feature Extraction. Paper presented at the the 21st International Conference on Pattern Recognition ICPR, Tsukuba, Japan.
35. Wang, S.-J., Yang, J., Sun, M.-F., Peng, X.-J., Sun, M.-M., & Zhou, C.-G. 2012. Sparse Tensor Discriminant Color Space for ce Verification. IEEE Transactions on Neural Networks and Learning Systems, 236, 876-888. doi: 10.1109/tnnls.2012.2191620
36. 周春光, 孙明芳,王苏菁, 陈前, 刘小华, & 刘昱昊. 2012. 基于稀疏张量的人脸图像特征提取方. 吉林大学学报工学版, 426, 1521-1526.
37. Chen, H.-L., Liu, D.-Y., Yang, B., Liu, J., Wang, G., &Wang, S.-J. 2011. An Adaptive Fuzzy k-Nearest Nei**or Method Based on Parallel Particle Swarm Optimization for Bankruptcy Prediction. Paper presented at the the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining PAKDD2011, Shenzhen, China.
38. Chen, H.-L., Yang, B., Wang, G., Liu, J., Xu, X.,Wang, S.-J., & Liu, D.-Y. 2011. A novel bankruptcy prediction model based on an adaptive fuzzy k-nearest nei**or method. Knowledge-Based Systems, 248, 1348-1359. doi: 10.1016/j.knosys.2011.06.008
39. Liu, Y., Wang, G., Chen, H., Dong, H., Zhu, X., &Wang, S.-J.2011. An Improved Particle Swarm Optimization for Feature Selection. Journal of Bionic Engineering, 82, 191-200. doi: 10.1016/S1672-65291160020-6
40. Sun, M.-F.,Wang, S.-J., Liu, X.-H., Jia, C.-C., & Zhou, C.-G. 2011. Human Action Recognition Using Tensor Principal Component ysis. Paper presented at the the 4th IEEE International Conference on Computer Science and Information Technology.
41. Wang, S.-J., Yang, J., Zhang, N., & Zhou, C.-G. 2011. Tensor Discriminant Color Space for ce Recognition. IEEE Transactions on Image Processing, 209, 2490-2501. doi: 10.1109/TIP.2011.2121084
42. Wang, S.-J., Chen, H.-L., Peng, X.-J., & Zhou, C.-G. 2011. Exponential locality preserving projections for all sample size problem. Neurocomputing, 7417, 3654-3662. doi: 10.1016/j.neucom.2011.07.007
43. Wang, S.-J., Zhou, C.-G., Chen, Y.-H., Peng, X.-J., Chen, H.-L., Wang, G., & Liu, X. 2011. A novel ce recognition method based on sub-pattern and tensor. Neurocomputing, 7417, 3553-3564. doi: 10.1016/j.neucom.2011.06.017
44. Wang, S.-J., Zhou, C.-G., Zhang, N., Peng, X.-J., Chen, Y.-H., & Liu, X. 2011. ce recognition using second-order discriminant tensor subspace ysis. Neurocomputing, 7412-13, 2142-2156. doi: 10.1016/j.neucom.2011.01.024
45. Wang, S.-J., Jia, C.-C., Chen, H.-L., & Zhou, C.-G. 2011. Matrix Exponential LPP for ce Recognition. Paper presented at the the First Asian Conference on Pattern Recognition ACPR, Beijing, China.
46. Wang, S.-J., Zhou, C.-G., Sun, M.-F., Chen, H.-L., Liu, X.-H., & Peng, X.-J. 2011. Can Estimate Age Range Using a ce a Person? Journal of Computational Information Systems, 713, 4586-4593.
47. Wang, S.-J., Zhang, N., Peng, X.-J., & Zhou, C.-G. 2011. Two-dimensional Locality Preserving Projection Based on Maximum Scatter Difference. Journal of Information and Computational Science, 83, 484-494.
48. Wang, S.-J., Zhang, N., Sun, M.-F., & Zhou, C.-G. 2011. The ysis of Parameters t and k of LPP on Several mous ce Databases. Paper presented at the the Second International Conference on Swarm Intelligence.
49. 陈前,王苏菁, 刘小华, 高蕾, & 周春光. 2011. 一种快速的虹膜定位算. 吉林大学学报理学版, 4906, 1095-1100.
50. 刘小华, 石娜,王苏菁, & 李春玲. 2011. 复杂背景下同光度性质物体的图像分割. 吉林大学学报理学版, 4905, 901-905.
51. 王苏菁, 周春光, 张娜, 李建朋, & 张利彪. 2011. 一种基于形状和纹理特征的人脸年龄估计方. 吉林大学学报工学版, 415, 1383-1387.
52. 张德才, 周春光, 周强, 池淑珍, &王苏菁. 2011. 基于廓的孔洞填充算. 吉林大学学报理学版, 491, 82-86.
53. Jia, C.-C.,Wang, S.-J., Xu, X., Zhou, C.-G., & Zhang, L. 2010. Tensor ysis and multi-scale features based multi-view human action recognition. Paper presented at the the Second International Conference on Computer Engineering and Technology ICCET. 10.1109/ICCET.2010.5485732%/ 2011-05-04 23:55:00
54. Wang, S.-J., Zhang, D.-C., Jia, C.-C., Zhang, N., Zhou, C.-G., & Zhang, L.-B. 2010. A Sign Language Recognition Based on Tensor. Paper presented at the the Second International Conference on Multimedia and Information Technology MMIT. 10.1109/MMIT.2010.21%/ 2011-07-14 09:09:00
55. Zhang, L., Xu, X.,Wang, S.-J., Ma, M., Zhou, C.-G., & Sun, C. 2010. Solved Environmental/Economic Dispatch Based on Multi-objective PSO. Paper presented at the the 2010 International Conference on Intelligent Computation Technology and Automation ICICTA. 10.1109/ICICTA.2010.470%/ 2010-08-19 18:06:00
56. Zhang, L., Xu, X.,Wang, S.-J., Zhou, C.-G., & Sun, C. 2010. Environmental/Economic Dispatch using a improved Differential Evolution. Paper presented at the the Second International Conference on Computer Engineering and Technology ICCET.
57. 陈震, 张娜, &王苏菁. 2010. 一种基于概念矩阵的概念格生成算. 计算机科学, 379, 180-183.