Signal Processing Image Communication

2.8k papers and 42.6k indexed citations i.

About

The 2.8k papers published in Signal Processing Image Communication in the last decades have received a total of 42.6k indexed citations. Papers published in Signal Processing Image Communication usually cover Computer Vision and Pattern Recognition (2.5k papers), Signal Processing (790 papers) and Media Technology (456 papers) specifically the topics of Video Coding and Compression Technologies (636 papers), Advanced Vision and Imaging (627 papers) and Advanced Data Compression Techniques (582 papers). The most active scholars publishing in Signal Processing Image Communication are Alan C. Bovik, Guojun Lu, Masayuki Tanimoto, Hua Huang, Lixiong Liu, Zhou Wang, Ligang Lu, Michael Hötter, Jörn Östermann and Rajan Joshi.

In The Last Decade

Fields of papers published in Signal Processing Image Communication

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Signal Processing Image Communication. 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 Signal Processing Image Communication.

Countries where authors publish in Signal Processing Image Communication

Since Specialization
Citations

This map shows the geographic impact of research published in Signal Processing Image Communication. 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 Signal Processing Image Communication with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Signal Processing Image Communication more than expected).

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.

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