Best wavelet packet bases in a rate-distortion sense
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doi.org/10.1109/83.217221 →Countries where authors are citing Best wavelet packet bases in a rate-distortion sense
This map shows the geographic impact of Best wavelet packet bases in a rate-distortion sense. 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 Best wavelet packet bases in a rate-distortion sense with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Best wavelet packet bases in a rate-distortion sense more than expected).
Fields of papers citing Best wavelet packet bases in a rate-distortion sense
This network shows the impact of Best wavelet packet bases in a rate-distortion sense. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Best wavelet packet bases in a rate-distortion sense.
About Best wavelet packet bases in a rate-distortion sense
This paper, published in 1993, received 529 indexed citations . Written by Kannan Ramchandran and Martin Vetterli covering the research area of Applied Mathematics and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (487 citations), Signal Processing (281 citations), Media Technology (81 citations), Computational Mechanics (35 citations) and Electrical and Electronic Engineering (32 citations). Published in IEEE Transactions on Image Processing.
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.
This paper is also available at doi.org/10.1109/83.217221.