EURASIP Journal on Image and Video Processing · 1×
×0.68k/13kCVPR
×0.62k/3kMT
×1.1906/848HI
×0.51k/2kSP
×0.92k/2kAI
Citations per year
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Countries where authors publish in IET Computer Vision
Since Specialization
Citations
This map shows the geographic impact of research published in IET Computer Vision. 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 papers published in IET Computer Vision with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites IET Computer Vision more than expected).
This network shows the impact of papers published in IET Computer Vision. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in IET Computer Vision.
About IET Computer Vision
The 1.1k papers published in IET Computer Vision in the last decades have received a total of 12.4k indexed citations . Papers published in IET Computer Vision usually cover Computer Vision and Pattern Recognition (971 papers), Media Technology (161 papers), Human-Computer Interaction (71 papers), Signal Processing (85 papers) and Artificial Intelligence (205 papers) specifically the topics of Video Surveillance and Tracking Methods (256 papers), Advanced Image and Video Retrieval Techniques (222 papers), Advanced Vision and Imaging (172 papers), Human Pose and Action Recognition (164 papers), Face and Expression Recognition (133 papers), Face recognition and analysis (113 papers), Robotics and Sensor-Based Localization (108 papers) and Advanced Neural Network Applications (101 papers). The most active scholars publishing in IET Computer Vision are S. Murugavalli, Saleh Aly, M. Hassaballah, Lei Zhang, Jifeng Ning, M. K. Bhuyan, David Zhang, Yuntao Qian, Lei Wang and Graham Leedham.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.