A Model for Learning the Semantics of Pictures
Impact in
Classified as
- Journal
- ScholarWorks@UMassAmherst (University of Massachusetts Amherst)
In The Last Decade
doi.org/w51085877 →Countries where authors are citing A Model for Learning the Semantics of Pictures
This map shows the geographic impact of A Model for Learning the Semantics of Pictures. 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 Model for Learning the Semantics of Pictures with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A Model for Learning the Semantics of Pictures more than expected).
Fields of papers citing A Model for Learning the Semantics of Pictures
This network shows the impact of A Model for Learning the Semantics of Pictures. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A Model for Learning the Semantics of Pictures.
About A Model for Learning the Semantics of Pictures
This paper, published in 2003, received 550 indexed citations . Written by Victor Lavrenko, R. Manmatha and Jiwoon Jeon covering the research area of Molecular Biology and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (535 citations), Artificial Intelligence (133 citations), Media Technology (100 citations), Molecular Biology (44 citations) and Computational Theory and Mathematics (10 citations). Published in ScholarWorks@UMassAmherst (University of Massachusetts Amherst).
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/w51085877.