师资队伍

副教授 学院首页 > 师资队伍 > 副教授 > 正文
刘春生

作者:   时间:2018-12-17   点击数:
姓名: 刘春生 undefined
                                           
性别:
民族: 汉族
出生年月: 1986.03
学历: 博士
职称: 副教授
导师信息: 硕士生导师
研究专业: 模式识别与智能系统
邮箱: liuchunsheng@sdu.edu.cn
个人主页: http://faculty.sdu.edu.cn/liuchunsheng/zh_CN/index.htm
所在院系: best365网页版登录官方网站控制科学与工程学院
研究方向: 模式识别、人工智能、无人驾驶和智能驾驶技术、机器人视觉
通信地址: 济南市经十路17923号best365网页版登录官方网站千佛山校区控制科学与工程学院

[1] 山东省自动化学会人工智能专委会副秘书长;

[2] 2017年山东省优秀博士论文, 复杂大背景下交通标志快速鲁棒的检测和识别研究,第1位;

[3] 美国电气和电子工程师协会IEEE Member

[4]   20209月,“best365网页版登录官方网站未来计划”入选者。

主要学习与工作经历:

2019至今 best365网页版登录官方网站,控制科学与工程学院,副教授,硕导

2018-2019,美国University of Washington,博士后

2016-2019,best365网页版登录官方网站,控制科学与工程学院,助理研究员,博士后

2005-2016,best365网页版登录官方网站,控制理论与控制工程,本硕博

主持科研项目

1.基于人作业意图的机器人互助任务智慧生成与应用,科技部重点研发计划。

2.智能驾驶人机互助混合增强智能关键技术研究,山东省重大创新研发项目。

3.基于显著性混合级联和深度网络树的智能驾驶多目标检测与跟踪,国家自然科学基金项目。

4.基于非对称学习和深度特征挖掘的智能驾驶场景车辆检测及定位研究,山东省自然科学基金项目。

5.动态大场景下共融型移动操作机器人交互安全性问题研究,国家自然科学基金项目

代表性论著目录                      

1.Chunsheng Liu and Faliang Chang, Hybrid Cascade Structure for License Plate Detection in Large Visual Surveillance Scenes, IEEE Transactions on Intelligent Transportation Systems, 20 (6), 2019: 2122-2135.

2.Chunsheng Liu, Faliang Chang, Zhenxue Chen and Dongmei Liu, Fast Traffic Sign Recognition via High-Contrast Region Extraction and Extended Sparse Representation, IEEE Trans. on Intelligent Transportation Systems, 2016, 17(1): 79-92.

3.Chunsheng Liu, Faliang Chang, Zhenxue Chen. Rapid Multiclass Traffic Sign Detection in High-Resolution Images, IEEE Trans. on Intelligent Transportation Systems, 2014, 15(6): 2394-2403.

4.Chunsheng Liu, Shuang Li, Faliang Chang, and Yinhai, Wang, Machine Vision Based Traffic Sign Detection Methods: Review, Analyses and Perspectives, IEEE Access, 7, 2019: 86578-86596.

5.Wang Zhang, Chunsheng Liu*, Faliang Chang and Ye Song, Multi-Scale and Occlusion Aware Network for Vehicle Detection and Segmentation on UAV Aerial Images, Remote Sensing. 2020, 12(11), 1760.

6.Chunsheng Liu, Yu Guo, Shuang Li, and Faliang Chang, ACF Based Region Proposal Extraction for YOLOv3 Network Towards High-performance Cyclist Detection in High Resolution Images, Sensors, 19 (2671), 2019: 1-18.

7.Chunsheng Liu, Shuang Li, Faliang Chang, and Wenhui, Dong, Supplemental Boosting and Cascaded ConvNet Based Transfer Learning Structure for Fast Traffic Sign Detection in Unknown Application Scenes, Sensors, 18 (2386), 2018: 1-19.

8.Chunsheng Liu, Faliang Chang. Multiview road sign detection via self-adaptive color model and shape context matching. Journal of Electronic Imaging, 2016, 25(5): 051202.

9.Faliang Chang, Chunsheng Liu*. High-performance Chinese multiclass traffic sign detection via coarse-to-fine cascade and parallel support vector machine detectors. Journal of Electronic Imaging, 2017, 26(5):053020.

10.Chunsheng Liu, Faliang Chang, Fast and robust region of interest extraction for Chinese road signs, Chinese Automation Congress (CAC) 2017, pp. 2877-2881, 2017.

11.Chunsheng Liu, Faliang Chang, Chengyun Liu. Cascaded split-level colour Haar-like features for object detection, IET Electronic letters, 2015, 51(25): 2106-2107.

12.Chunsheng Liu, Faliang Chang, Chengyun Liu. Multiview road sign detection via self-adaptive color model and shape context matching, Journal of Electronic Imaging, 2016, 25(5).

13.Chunsheng Liu, Faliang Chang, Chengyun Liu. Occlusion-Robust Traffic Sign Detection via Cascaded Color Cubic Feature, IET Intelligent Transport Systems, accepted in Dec. 2015, to be published.

14.Chunsheng Liu, Faliang Chang, Zhenxue Chen. Rapid Traffic Sign Detection and Classification Using Categories-first-assigned Tree, Journal of Computational Information Systems, 2013, 9(18): 7461-7468.

15.Chunsheng Liu, Faliang Chang, Zhenxue Chen. High performance traffic sign recognition based on sparse representation and SVM classification, ICNC, July, Xiamen, 2014: 108-112.

授权发明专利                                

1.刘春生,一种基于像素级联特征的模糊车牌检测方法, ZL201410088991.3.

2.刘春生一种基于对比色矩形特征的小尺寸车牌检测方法ZL201710021867.9.

上一条:郭庆强

下一条:王正方

©2019beat365·体育官网(中文版)登录入口 best365网页版登录官方网站千佛山校区
山东省济南市经十路17923号 邮编250061