Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
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doi.org/10.1016/j.inffus.2021.11.006 →Countries where authors are citing Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This map shows the geographic impact of Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges more than expected).
Fields of papers citing Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This network shows the impact of Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges.
About Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges
This paper, published in 2021, received 483 indexed citations . Written by Sen Qiu, Hongkai Zhao, Nan Jiang, Zhelong Wang, Long Liu, Yi An, Hongyu Zhao, Xin Miao, Ruichen Liu and Giancarlo Fortino covering the research area of Artificial Intelligence, Biomedical Engineering and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (190 citations), Biomedical Engineering (149 citations), Artificial Intelligence (124 citations), Computer Networks and Communications (54 citations) and Electrical and Electronic Engineering (46 citations). Published in Information Fusion.
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This paper is also available at doi.org/10.1016/j.inffus.2021.11.006.