Axioms and fundamental equations of image processing

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About

This paper, published in 1950, received 623 indexed citations. Written by Luis Álvarez, Pierre Louis Lions and Jean‐Michel Morel covering the research area of Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (421 citations), Computational Mechanics (167 citations) and Computational Theory and Mathematics (91 citations). Published in Archive for Rational Mechanics and Analysis.

Countries where authors are citing Axioms and fundamental equations of image processing

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This map shows the geographic impact of Axioms and fundamental equations of image processing. 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 Axioms and fundamental equations of image processing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Axioms and fundamental equations of image processing more than expected).

Fields of papers citing Axioms and fundamental equations of image processing

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Axioms and fundamental equations of image processing. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Axioms and fundamental equations of 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/10.1007/bf00375127.

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