WANG Yexin
Professional Title：Associate Professor
Phone：010-64807987
Email：wangyx@aircas.ac.cn
Dr. Wang is currently an associate researcher at the State Key Laboratory of Remote Sensing and Digital Earth, Aerospace Information Research Institute,Chinese Academy of sciences. She received the Ph.D. degree in measuring and testing technologies and instruments from Beihang University, Beijing, China, in 2014.
Planetary remote sensing, artificial intelligence theory and application, and lunar laser ranging.
Main research projects
1) Youth Program of National Natural Science Foundation of China，research on Mars dark slope streaks deep feature description and automatic identification method, 2018/1-2020/12, PI.
2) Binocular visual environment perception, 2018/4-2019/12, PI.
3) Key Research Program of the Chinese Academy of Sciences,2018/6-2020/12, participate.
4) National Key Research and Development Program of China, Multi-sources indoor intelligent positioning technology, 2016/1-2020/12, participate.
5) Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, comparison research on planet and earth surface changes based on remote sensing, 2016/1-2020/12, participate.
6) Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, research on high-precision three-dimensional digitalization using structured light and stereo vision, 2015/1-2016/12, PI.
7) National Natural Science Foundation of China, Study on Photogrammetry Model for Light Field Camera, 2015/1-2018/12, participate.
[1] Wang, Y., Nan, J., Zhao, C., Xie, B., Gou, S., Yue, Z., Di, K., Zhang, H., Deng, X., Sun, S. A Catalogue of Impact Craters and Surface Age Analysis in the Chang’e-6 Landing Area. Remote Sensing, 2024, 16, 2014.
[2] Nan, J.; Wang, Y*.; Di, K.; Xie, B.; Zhao, C.; Wang, B.; Sun, S.; Deng, X.; Zhang, H.; Sheng, R. YOLOv8-LCNET: An Improved YOLOv8 Automatic Crater Detection Algorithm and Application in the Chang’e-6 Landing Area. Sensors, 2025, 25, 243.
[3 ]Liu, Y., Wang, Y.*, Di, K., Peng, M., Wan. W., Liu, Z. A Generative Adversarial Network for Pixel-Scale Lunar DEM Generation from High-Resolution Monocular Imagery and Low-Resolution DEM, Remote Sensing, 2022,14, 5420.
[4] Wang Y., Wan W., Gou S., Peng M., Liu Z., Di K., Li L., Yu T., Wang J., Cheng X. Vision-Based Decision Support for Rover Path Planning in the Chang’e-4 Mission. Remote Sensing, 2020, 12: 624.
[5] Wang, Y., Di, K., Xin, X., Wan, W. Automatic detection of Martian dark slope streaks by machine learning using HiRISE images. ISPRS Journal of Photogrammetry and Remote Sensing, 2017, 129: 12-20.
