汪校锋
Supervisor of Master's Candidates
Gender : Male
Alma Mater : 中国地质大学(武汉)
Education Level : Faculty of Higher Institutions
Degree : 博士学位
Status : Employed
School/Department : 计算机学院
Date of Employment : 2005-07-01
Discipline : Spatial information and digital technology
Contact Information : wxf@cug.edu.cn
Email :
Hits :
Included Journals : EI
Affiliation of Author(s): 计算机学院
Discipline : Engineering
First-Level Discipline : Computer
Document Type : J
Indexed by : Journal paper
Translation or Not : no
Place of Publication : USA
Key Words : Feedback embedding, hyperspectral image (HSI), pixel awareness, recurrent network, super-resolution
Abstract : Hyperspectral images (HSIs) contain abundant spectral information, while the spatial resolution is usually limited. To
obtain high-spatial-resolution HSIs, various HSI super-resolution
(SR) methods are proposed. Currently, deep-learning-based SR
reconstruction methods are studied in depth, which take different
measures to make full use of the spatial and spectral information
of HSIs, and optimize the network with lots of trainings. Although
they have achieved satisfying spatial resolution, the spectral consistency before and after reconstruction is difficult to guarantee. In
this article, we
Correspondence Author : Ruyi Feng, Zhongyu Guo and Xiaofeng Wang*
Author : Xiaofeng Wang
Pre One : Xiaofeng Wang, Zhongyu Guo and Ruyi Feng. A CNN- and Transformer-Based Dual-Branch Network for Change Detection with Cross-Layer Feature Fusion and Edge Constraints. Remote Sensing, 16, 2573, 2024.(T2)
Next One : Qin Xuewen, Feng Bangguo, Zhang Yun, Wang Xiaofeng. Rock-Soil Geochemical Background Characteristics and Prospecting Significance of Duancun Area in Western Henan Provence. Xinjiang Geology(in Chinese), 41(1): 46-50, 2023.
Xiaofeng Wang, male, studied and worked at China University of Geosciences (Wuhan). He obtained a PhD in Structural Geology in 2015 respectively. From 2015 to 2017, he was a visiting scholar at the University of Windsor in Canada. After graduating in 2005, he remained at the university to engage in geological surveys and scientific research management. During his work, he undertook or participated in 20 research projects and published more than 15 academic papers. His fields of interests are deep learning for remote sensing, semi-automated lineament detection and geoscience information engineering.