基本信息

姓 名 : 邵秀丽

性 别 :

所属部门: 计算机科学与技术系

行政职务:

职 称 : 教授

学 历 : 博士

所学专业: 计算机软件

办公电话: 23509121

电子邮件: shaoxl@nankai.edu.cn

研究方向: 人工智能、数据分析、智能系统、CSCW协同控制

个人简介:

从事教师工作几十年,先后承担和参加国家自然科学基金、国家863项目、天津市自然科学基金、天津市重点研究项目等多项科研项目,并取得了大量的与本项目相关的研究成果。曾获十余项省部级科研项目奖励,最近几年的主要有2018 年度吴文俊人工智能科学技术奖,2019 年度天津市科学技术进步二等奖等奖励。从90年代教学人工智能课程、高级程序设计语言、离散数学等课程。博士招生方向为人工智能、软件工程方向,目前的科研课题主要聚焦人工智能、软件工程领域。在研项目有:科技部重点研发:人工耳蜗植入机理建模及机器人手术入路设计与研究;国基金面上项目:面向视觉覆盖优化的多机器人空地协同轨迹规划方法研究;天津市:基于智能技术的风机转子质量检测等6项;近两年代表性论文:[1]LC3Net: Ladder context correlation complementary network for salient object detection[J]. Knowledge-Based Systems.

[2]IBNet: Interactive branch network for salient object detection[J]. Neurocomputing, 2021, 465: 574-583.

[3]Subspace clustering with block diagonal sparse representation[J]. Neural Processing Letters, 2021, 53: 4293-4312.

[4]Collaborative learning in bounding box regression for object detection[J]. Pattern Recognition Letters, 2021, 148: 121-127.

[5]A plug and play fast intersection over union loss for boundary box regression[C]//Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2021: 1705-1709.

[6] Lightweight boundary refinement module based on point supervision for semantic segmentation[J]. Image and Vision Computing, 2021, 110: 104169.

[7]Rotor surface defect and symmetry detection based on point cloud registration[C]//Proceedings of the IEEE International Conference on Power Electronics, Computer Applications (ICPECA). 2021.

[8] Improved filtering and hole filling algorithm for the point cloud of rotor surface based on PCL[C]//Proceedings of the IEEE International Conference on Power Electronics, Computer Applications (ICPECA). 2021.

[9] Learning sparse features with lightweight ScatterNet for small sample training[J]. Knowledge-Based Systems, 2020, 205: 106315.

[10] An improved morphological algorithm for defect detection on point cloud data[C]//Proceedings of the IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS). 2020, pp. 13-17.

[11]Dynamic attention graph convolution neural network of point cloud segmentation for defect detection[C]//Proceedings of the IEEE International Conference on Artificial Intelligence and Information Systems (ICAIIS). 2020, pp. 18-23.

[12]Lightweight boundary refinement module based on point supervision for semantic segmentation[J]. Image and Vision Computing, 2021, 110: 104169.