Object detection and 3D reconstruction with mobile mapping data
Semantic classification is a traditional research topic in both computer vision and remote sensing areas. With the development and common use of deep learning, image understanding gains relatively high accuracy and stability from big data, but still face challenges on accuracy promotion when processing the complex image scene such as city with high-density buildings, and on workflow simplification such as directly output of mapping results.
My current research focuses on automatic 3D reconstruction, semantic labeling and mapping with machine learning, which aims to make fully use of 3D information from stereo images and the power of AI. The research would help applications including earth surface surveying, city mapping and mobile sensing for autonomous driving.
- Engineer, China Transport Telecommunications & Information Center, 2015-2019
- Ph.D., Photogrammetry and Remote Sensing, Wuhan University, 2015.
- M.Sc., Photogrammetry and Remote Sensing, Wuhan University, 2011
- B.Sc., Photogrammetry, Wuhan University, 2009
- Pan Y.F., Zhang X.F., Tian J., Jin X., Luo L., Yang K., 2017. Mapping asphalt pavement aging and condition using multiple endmember spectral mixture analysis in Beijing, China. Journal of Applied Remote Sensing, 11(1), 016003.
- Zhang, J.X, Yang, K., 2015. Informational analysis for compressive sampling in radar imaging, Sensors, 15(4): 7136-7155.
- Zhang, J.X, Yang, K., Liu, F., Zhang, Y., 2015. Information-theoretic characterization and undersampling ratio determination for compressive radar imaging in a simulated environment, Entropy, 17(8): 5171-5198.
- Guo, J.Z., Zhang, J.X., Yang, K., 2015. Information capacity and sampling ratios for compressed sensing-based SAR imaging, IEEE Geoscience and Remote Sensing Letters, 12(4): 900-904.
- Zhang, J.X, Yang, K., Guo, J.Z., 2014. Information theoretic bounds for compressed sensing in SAR imaging. IOP Conference Series: Earth and Environmental Science, 17 012273.
- Zhang, J.X., Yang, K., Guo, J.Z., 2014. Information-theoretic interpretations of compressive sampling. Geomatics and Information Sciences of Wuhan University, 39(11).