王臣 - 南京信息工程大学

个人简介

教育背景： 2009.09—2013.06 中国地质大学，遥感科学与技术，本科 2013.09—2016.06 中国海洋大学，摄影测量与遥感，硕士 2016.10—2020.07 法国海洋开发研究院 (Ifremer)，物理海洋与环境，博士工作经历： 2020.11—至今南京信息工程大学，讲师教育经历 2016.10-2020.7 法国海洋开发研究院（Ifremer）物理海洋与环境博士 2013.9-2016.6 中国海洋大学摄影测量与遥感硕士 2009.9-2013.6 中国地质大学遥感科学与技术学士

研究领域

海洋大气边界层；微波海洋遥感；海洋大数据与机器学习

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）

数据集： [1] C. Wang* et al., “Labeled SAR imagery dataset of ten geophysical phenomena from Sentinel-1 wave mode (TenGeoP-SARwv).” SEA scieNtific Open data Edition (SEANOE), 2018, doi: 10.17882/56796. 期刊论文： [6] C. Wang*, D. Vandemark, A. Mouche, B. Chapron, H. Li, and R. C. Foster, “An assessment of marine atmospheric boundary layer roll detection using Sentinel-1 SAR data,” Remote Sens. Environ., vol. 250, p. 112031, Dec. 2020, doi: 10.1016/j.rse.2020.112031. [5] C. Wang* et al., “Classification of the global Sentinel-1 SAR vignettes for ocean surface process studies,” Remote Sens. Environ., vol. 234, p. 111457, Dec. 2019, doi: 10.1016/j.rse.2019.111457. [4] C. Wang* et al., “A labelled ocean SAR imagery dataset of ten geophysical phenomena from Sentinel‐1 wave mode,” Geosci. Data J., vol. 6, no. 2, pp. 105–115, Nov. 2019, doi: 10.1002/gdj3.73. [3] S. Song, C. Zhao, W. An, X. Li, and C. Wang, “Analysis of impacting factors on polarimetric SAR oil spill detection,” Acta Oceanol. Sin., vol. 37, no. 11, pp. 77–87, Nov. 2018, doi: 10.1007/s13131-018-1335-9. [2] C. Wang, C. Zhao*, K. Zeng, and Y. Wang, “Analysis of scattering mechanisms over sea oil slicks based on eigenvalues of simplified coherence matrix,” J. Appl. Remote Sens., vol. 9, no. 1, p. 95974, 2015, doi: 10.1117/1.JRS.9.095974. [1] 王臣, 刘朋*, 赵朝方, 和崔文连, “高分一号在青岛输油管道海面溢油监测中的应用,” 海洋湖沼通报, no. 04, pp. 174–179, 2014. 会议论文： [2] C. Wang* et al., “Characteristics of Marine Atmospheric Boundary Layer Roll Vortices from Sentinel-1 Sar Wave Mode,” in IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Jul. 2019, pp. 7908–7911, doi: 10.1109/IGARSS.2019.8900287. [1] C. Wang* et al., “Automated Geophysical Classification of Sentinel-1 Wave Mode SAR Images Through Deep-Learning,” in IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Jul. 2018, pp. 1776–1779, doi: 10.1109/IGARSS.2018.8518354.