The PASCAL visual object classes challenge 2006 (VOC2006) results
In The Last Decade
doi.org/w89990256 →Countries where authors are citing The PASCAL visual object classes challenge 2006 (VOC2006) results
This map shows the geographic impact of The PASCAL visual object classes challenge 2006 (VOC2006) results. 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 The PASCAL visual object classes challenge 2006 (VOC2006) results with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites The PASCAL visual object classes challenge 2006 (VOC2006) results more than expected).
Fields of papers citing The PASCAL visual object classes challenge 2006 (VOC2006) results
This network shows the impact of The PASCAL visual object classes challenge 2006 (VOC2006) results. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the The PASCAL visual object classes challenge 2006 (VOC2006) results.
About The PASCAL visual object classes challenge 2006 (VOC2006) results
This paper, published in 2006, received 1.7k indexed citations . Written by Mark Everingham, Andrew Zisserman, Christopher K. I. Williams and Luc Van Gool covering the research area of Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (1.5k citations), Artificial Intelligence (481 citations) and Aerospace Engineering (209 citations).
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/w89990256.