Factor Graphs for Robot Perception

268 indexed citations
published 2017
Authors
Frank DellaertMichael Kaess

In The Last Decade

doi.org/10.1561/2300000043 →

Countries where authors are citing Factor Graphs for Robot Perception

Specialization
Citations

This map shows the geographic impact of Factor Graphs for Robot Perception. 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 Factor Graphs for Robot Perception with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Factor Graphs for Robot Perception more than expected).

Fields of papers citing Factor Graphs for Robot Perception

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Factor Graphs for Robot Perception. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Factor Graphs for Robot Perception.

About Factor Graphs for Robot Perception

This paper, published in 2017, received 268 indexed citations . Written by Frank Dellaert and Michael Kaess covering the research area of Control and Systems Engineering, Aerospace Engineering and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Aerospace Engineering (212 citations), Computer Vision and Pattern Recognition (110 citations) and Electrical and Electronic Engineering (85 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/10.1561/2300000043.

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