M. Abdelkareem, S. Auer, A. B. Pour, Jianguo Chen, Jian Cheng, M. Datcu, Huihui Feng, Shubham Gupta, M. Hashim, Maryam Imani, W. Kainz, M. S. Karoui, T. Kavzoglu, Fatemeh Kowkabi, Anil Kumar, Xue Li, Zengke Li, Feng
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引用次数: 0
Abstract
The editors of the International Journal of Image and Data Fusion wish to express their sincere gratitude to the following reviewers for their valued contribution to the journal in 2021. Mohamed Abdelkareem Stefan Auer Amin Beiranvand Pour Jianguo Chen Jian Cheng Mihai Datcu Huihui Feng Shubham Gupta Mazlan Hashim Maryam Imani Wolfgang Kainz Moussa Sofiane Karoui Taskin Kavzoglu Fatemeh Kowkabi Anil Kumar Xue Li Zengke Li Feng Ling Zhong Lu Arash Malekian Lamin R. Mansaray Seyed Jalaleddin Mousavirad Mircea Paul Muresan Henry Y.T. Ngan Mohammad Parsa Shengliang Pu Jinxi Qian Omeid Rahmani H. Ranjbar Wellington Pinheiro dos Santos Hadi Shahriari Huanfeng Shen Yuqi Tang Kishor Upla INTERNATIONAL JOURNAL OF IMAGE AND DATA FUSION 2021, VOL. 12, NO. 4, i–ii https://doi.org/10.1080/19479832.2021.1995136
《国际图像与数据融合杂志》的编辑们衷心感谢以下审稿人在2021年为该杂志做出的宝贵贡献。Mohamed Abdelkareem Stefan Auer Amin Beiranvand Pour Jianguo Chen Jian Cheng Mihai Datcu Huizui Feng Shubham Gupta Mazlan Hashim Maryam Imani Wolfgang Kainz Moussa Sofiane Karoui Taskin Kavzoglu Fatemeh Kowkabi Anil Kumar Xue Li Zengke Li Feng Ling Zhong Lu Arash Malekian Lamin R。Mansaray Seyed Jalaleddin Mousavirad Mircea Paul Muresan Henry Y.T.Ngan Mohammad Parsa Shengliang Pu Jinxi Qian Omeid Rahmani H.Ranjbar Wellington Pinheiro dos Santos Hadi Shahriari Huanfeng Shen Yuqi Tang Kishor Upla INTERNATIONAL JOURNAL OF IMAGE AND DATA FUSION 2021，第12卷，第4期，i–iihttps://doi.org/10.1080/19479832.2021.1995136
期刊介绍：
International Journal of Image and Data Fusion provides a single source of information for all aspects of image and data fusion methodologies, developments, techniques and applications. Image and data fusion techniques are important for combining the many sources of satellite, airborne and ground based imaging systems, and integrating these with other related data sets for enhanced information extraction and decision making. Image and data fusion aims at the integration of multi-sensor, multi-temporal, multi-resolution and multi-platform image data, together with geospatial data, GIS, in-situ, and other statistical data sets for improved information extraction, as well as to increase the reliability of the information. This leads to more accurate information that provides for robust operational performance, i.e. increased confidence, reduced ambiguity and improved classification enabling evidence based management. The journal welcomes original research papers, review papers, shorter letters, technical articles, book reviews and conference reports in all areas of image and data fusion including, but not limited to, the following aspects and topics: • Automatic registration/geometric aspects of fusing images with different spatial, spectral, temporal resolutions; phase information; or acquired in different modes • Pixel, feature and decision level fusion algorithms and methodologies • Data Assimilation: fusing data with models • Multi-source classification and information extraction • Integration of satellite, airborne and terrestrial sensor systems • Fusing temporal data sets for change detection studies (e.g. for Land Cover/Land Use Change studies) • Image and data mining from multi-platform, multi-source, multi-scale, multi-temporal data sets (e.g. geometric information, topological information, statistical information, etc.).
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