Information Fusion

雜志介紹

Information Fusion雜志介紹

《Information Fusion》是一本以English為主的未開放獲取國際優秀期刊，中文名稱信息融合，本刊主要出版、報道計算機科學-COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為14.7，最新CiteScore 指數為33.2。

本刊近期中國學者發表的論文主要有：

• Incremental unsupervised feature selection for dynamic incomplete multi-view data

  Author: Huang, Yanyong; Guo, Kejun; Yi, Xiuwen; Li, Zhong; Li, Tianrui

• TSK fuzzy system fusion at sensitivity-ensemble-level for imbalanced data classification

  Author: Zhang, Yuanpeng; Wang, Guanjin; Huang, Xiuyu; Ding, Weiping

• AT-GAN: A generative adversarial network with attention and transition for infrared and visible image fusion

  Author: Rao, Yujing; Wu, Dan; Han, Mina; Wang, Ting; Yang, Yang; Lei, Tao; Zhou, Chengjiang; Bai, Haicheng; Xing, Lin

• Rethinking multi-exposure image fusion with extreme and diverse exposure levels: A robust framework based on Fourier transform and contrastive learning

  Author: Qu, Linhao; Liu, Shaolei; Wang, Manning; Song, Zhijian

英文介紹

Information Fusion雜志英文介紹

The journal is intended to present within a single forum all of the developments in the field of multi-sensor, multi-source, multi-process information fusion and thereby promote the synergism among the many disciplines that are contributing to its growth. The journal is the premier vehicle for disseminating information on all aspects of research and development in the field of information fusion. Articles are expected to emphasize one or more of the three facets: architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.