徐其志 - 北京理工大学

个人简介

教育背景 2001年9月-2005年6月江西师范大学计算机学院计算机科学与技术专业，本科 2005年9月-2007年12月北京航空航天大学计算机学院计算机应用技术专业，硕士 2007年9月-2013年1月北京航空航天大学计算机学院计算机应用技术专业，博士工作经历 2013年3月-2015年3月加拿大University of New Brunswick，博士后 2015年3月-2018年12 北京航空航天大学计算机学院，副教授 2018年12月-2020年10 北京化工大学计算机学院，教授 2020年11月至今北京理工大学计算机学院，特别研究员社会兼职全国专业标准化技术委员会委员（SAC/TC 307） IEEE Trans. on Geosci. and Remote Sens.， IEEE Geosci. and Remote Sens. Lett， J. Applied Remote Sens.等期刊审稿人

研究领域

空天感知与智能计算，数据融合，遥感大数据分析

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Q. Xu, B. Li, et. al, “Multiscale contour extraction using a level set method in optical satellite images”, IEEE Geosci. and Remote Sens. Lett., 8(5): 854-858, 2011. Q. Xu, B. Li, et. al, “High-fidelity component substitution pansharpening by the fitting of substitution data”, IEEE Trans. on Geosci. and Remote Sens. , 52(11): 7380-7392, 2014. Q. Xu, Y. Zhang, B. Li, “Improved SIFT match for optical satellite images registration by size classification of blob-like structures”, Remote Sens. Lett., 5(5): 451-460, 2014. Q. Xu, Y. Zhang, B. Li, “Recent advances in pansharpening and key problems in applications”, Int. J. Image Data Fusion, 5: 175-195, 2014. Q. Xu, Y. Zhang, et. al, “Pansharpening using regression of classified MS and Pan images to reduce color distortion”, IEEE Geosci. and Remote Sens. Lett., 12(1): 28-32, 2015. L. Wang, Q. Dai, Q. Xu*, Y. Zhang, “Constructing hierarchical segmentation tree for feature extraction and land cover classification of high resolution MS imagery”, IEEE J. Selected Topics in Applied Earth Observ. and Remote Sens., 8(5): 1946-1961, 2015. X. Wang, Q. Xu*, et. al, “Robust and fast scale-invariance feature transform match of large-size multispectral image based on keypoint classification”, J. Applied Remote Sens., 9 (096028): 1-20, 2015. F. Gao, Q. Xu*, B. Li, “Robust aircraft segmentation from very high-resolution images based on bottom-up and top-down cue integration”, J. Applied Remote Sens., 10(016003): 1-11, 2016. Y. Wang, J. Zheng, Q. Xu, B. Li, H. Hu, “An improved RANSAC based on the scale variation homogeneity”, J. Visual Commun. and Image Represent., 40: 751-764, 2016. Q. Xu, W. Qiu, et. al, “Hyperspectral and panchromatic image fusion through an improved ratio enhancement”, J. Applied Remote Sens., 11(015017): 1-14, 2017. F. Yang, Q. Xu*, B. Li, “Ship detection from optical satellite images based on saliency segmentation and structure-LBP feature”, IEEE Geosci. and Remote Sens. Lett., 14(5): 602-606, 2017. F. Yang, Q. Xu*, B. Li, “Ship Detection from Thermal Remote Sensing Imagery through Region-based Deep Forest”, IEEE Geosci. and Remote Sens. Lett., 15(3): 449-453, 2018. J. Zheng , Q. Xu*, et. al, “The On-orbit Non-Cloud-Covered Water Region Extraction for Ship Detection based on Relative Spectral Reflectance”, IEEE Geosci. and Remote Sens. Lett., 15(6): 818-822, 2018. Li Q, Mou L., Xu Qizhi*, Zhang Y., Zhu X., “R3-Net: A Deep Network for Multi-oriented Vehicle Detection in Aerial Images and Videos”, IEEE Trans. on Geosci. and Remote Sens. , 2019, 25(6): 5028-5042. Y. Li, Qizhi Xu*, W. Li, J. Nie, “Automatic Clustering-Based Two-Branch CNN for Hyperspectral Image Classification”, IEEE Trans. on Geosci. and Remote Sens. , 2020, 0(0): 1-14. J. Nie, Qizhi Xu*, J. Pan, M. Guo, “Hyperspectral Image Classification Based on Multiscale Spectral–Spatial Deformable Network”, IEEE Geosci. and Remote Sens. Lett., 2020, 0(0): 1-5.