对2020年《国际图像与数据融合杂志》审稿人的致谢

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International Journal of Image and Data Fusion Pub Date : 2021-01-02 DOI:10.1080/19479832.2021.1874635

Farhang Aliyari, T. Bouwmans, Yinguo Cao, Yushi Chen, A. Cherukuri, Srinivasa Rao Dammavalam, Vaidehi Deshmukh, Songlin Du, A. Erturk, S. Goh, Qing Guo, Marcus Hammer, Zhaozheng Hu, Jincai Huang, Shuying Huang, Maryam Imani, A. Jenerowicz, Bin Jia, W. Kainz, Singara Singh Kasana, J. Keighobadi, M. F. A. Khanan, Beibei Li, Dong Li, Zengke Li, Huimin Liu, Menghua Liu, Qingjie Liu, Ran Liu, Shengheng Liu, Zhengyi Liu, D. Lizcano, D. Lu, Xiaocheng Lu, P. Marpu, Deepak Mishra, P. Nepa, Yi-Ning Ning, Teerapong Panboonyuen, Rakesh C. Patel, Z. Shao, Huan-si Shen, Weina Song, A. Stein, Jianbo Tang, Yunwei Tang, Ling Tong, J. Torres-Sospedra, Md Azher Uddin, Kishor P. Upla, Sowmya V jian wang, Mingwen Wang, Qi Wang, Siye Wang, Kai Wen, Mengquan Wu, Youxi Wu, Fu Xiao, Bo-Lun Xu, Gong-Tao Yan, Hongbo Yan, Feng-Mei Yang, Xue Yang, Yuegang Yu, X. Yuan, C. Yuen, Yun Zhang, Bobai Zhao, Wen-long Zhao, Chao Zhou, Guoqing Zhou, Haiyang Zhou, Weidong Zou

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引用次数: 0

摘要

Farhang Aliyari Thierry Bouwmans Ying Cao Yushi Chen Aswani Kumar Cherukuri Srinivasa Rao Dammavalam Vaidehi Deshmukh Sonlin Du Alp Erturk Shu Ting Goh Qing Guo Marcus Hammer Zhaozheng Hu Jincai Huang Shuying Huang Maryam Imani Agnieszka Jenerowicz Binghao Jia Wolfgang Kainz Singara Singh Kasana Jafar Keighobadi M.F。AbdulKhanan Beibei李东李增科李惠民刘萌刘庆杰刘然刘胜恒刘正义刘大卫Lizcano Dengsheng Lu国际图像与数据融合杂志2021，第12卷，第1期，i–iihttps://doi.org/10.1080/19479832.2021.1874635

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Acknowledgement to Reviewers of the International Journal of Image and Data Fusion in 2020

Farhang Aliyari Thierry Bouwmans Ying Cao Yushi Chen Aswani Kumar Cherukuri Srinivasa Rao Dammavalam Vaidehi Deshmukh Songlin Du Alp Erturk Shu Ting Goh Qing Guo Marcus Hammer Zhaozheng Hu Jincai Huang Shuying Huang Maryam Imani Agnieszka Jenerowicz Binghao Jia Wolfgang Kainz Singara Singh Kasana Jafar Keighobadi M. F. Abdul Khanan Beibei Li Dong Li Zengke Li Huimin Liu Meng Liu Qingjie Liu Ran Liu Shengheng Liu Zhengyi Liu David Lizcano Dengsheng Lu INTERNATIONAL JOURNAL OF IMAGE AND DATA FUSION 2021, VOL. 12, NO. 1, i–ii https://doi.org/10.1080/19479832.2021.1874635

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来源期刊

International Journal of Image and Data Fusion REMOTE SENSING-

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5.00

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发文量

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.).