汪路康讲师

遥感影像智能解译

  • 0532- 80698303
  • wanglukang@sdust.edu.cn

职称/职务:讲师

电话:0532-80698303

电子邮箱:wanglukang@sdust.edu.cn

办公地址:青岛市黄岛区前湾港路579号立博手机版登录入口进入J6楼344室

2014年9月- 2018年7月 中国矿业大学,学士;

2018年9月- 2024年7月 中国矿业大学,博士;

2019年3月- 2020年2月 香港理工大学,Research Assistant;

2023年4月- 2023年9月 香港理工大学,Research Assistant。

遥感影像智能解译

数字图像处理与分析

代表性论文1,Wang Lukang, Zhang Min, & Shi Wenzhong. CS-WSCDNet: Class Activation Mapping and Segment Anything Model-based Framework for Weakly Supervised Change Detection. IEEE Transactions on Geoscience and Remote Sensing, 2023, DOI: 10.1109/TGRS.2023.3330479.

代表性论文2,Wang Lukang, Zhang Min, Shen Xiaoqi, & Shi Wenzhong. Landslide Mapping Using Multilevel-Feature-Enhancement Change Detection Network. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023, DOI: 10.1109/JSTARS.2023.3245062.

代表性论文3,Wang Lukang, Zhang Min, & Shi Wenzhong. STCRNet: A Semi-Supervised Network Based on Self-Training and Consistency Regularization for Change Detection in Remote Sensing Images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, DOI: 10.1109/JSTARS.2023.3345017.

代表性论文4,Wang Lukang, Li Yue, Zhang Min, Shen Xiaoqi, Peng Wenguang, & Shi Wenzhong. MSFF-CDNet: A Multiscale Feature Fusion Change Detection Network for Bi-Temporal High-Resolution Remote Sensing Image. IEEE Geoscience and Remote Sensing Letters, 2023, DOI: 10.1109/LGRS.2023.3305623.

代表性论文5,Wang Lukang, Zhang Min, Gao Xu, & Shi Wenzhong. Advances and Challenges in Deep Learning-Based Change Detection for Remote Sensing Images: A Review through Various Learning Paradigms. Remote Sensing, 2024, DOI: 10.3390/rs16050804.

代表性论文6,Peng Wenguang, Shi Wenzhong, Zhang Min, & Wang Lukang. FDA-FFNet: A Feature-Distance Attention-Based Change Detection Network for Remote Sensing Image. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023, DOI: 10.1109/JSTARS.2023.3344633.

代表性论文7,Shen Xiaoqi, Shi Wenzhong, Chen Pengfei, Liu Zhewei, & Wang Lukang. Novel model for predicting individuals’ movements in dynamic regions of interest, GIScience & Remote Sensing, 2022, DOI: 10.1080/15481603.2022.2026637.

代表性论文8,Shen Xiaoqi, Shi Wenzhong, Liu Zhewei, Zhang Anshu, Wang Lukang, & Zeng Fanxin. Extracting Human Activity Areas from Large-Scale Spatial Data with Varying Densities. ISPRS International Journal of Geo-Information, 2022, DOI: 10.3390/ijgi11070397.