A geometric model for active contours in image processing
- Computational Mechanics
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
- Journal
- Numerische Mathematik
In The Last Decade
doi.org/10.1007/bf01385685 →Countries where authors are citing A geometric model for active contours in image processing
This map shows the geographic impact of A geometric model for active contours in 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 A geometric model for active contours in 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 A geometric model for active contours in image processing more than expected).
Fields of papers citing A geometric model for active contours in image processing
This network shows the impact of A geometric model for active contours in 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 A geometric model for active contours in image processing.
About A geometric model for active contours in image processing
This paper, published in 1993, received 1.2k indexed citations . Written by Vicent Caselles, Tomeu Coll and F. Dibos covering the research area of Computational Mechanics, Computer Graphics and Computer-Aided Design and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (1.0k citations), Computational Mechanics (176 citations) and Media Technology (157 citations). Published in Numerische Mathematik.
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/bf01385685.