Matthew Koichi Grimes

2.6k citations
3 papers · 1.4k indexed · 1 hit paper · h-index 3
Topics
Robotics and Sensor-Based Localization (3 papers)Advanced Vision and Imaging (2 papers)Advanced Image and Video Retrieval Techniques (2 papers)
Journals
arXiv (Cornell University)

In The Last Decade

Matthew Koichi Grimes

3 papers receiving 1.3k citations

Hit Papers

PoseNet: A Convolutional Network for Real-Time 6-DOF Came...201520262018202220154008001.2k

Peers

Matthew Koichi Grimes
Comparison fields: 5 of 88
  • Computer Vision and Pattern Recognition 1.1k
  • Aerospace Engineering 1.0k
  • Geology 218
  • Electrical and Electronic Engineering 169
  • Control and Systems Engineering 157
Replace Jürgen Hess with:
Jürgen Hess Germany
Matia Pizzoli Switzerland
Sören Schwertfeger China
J.-S. Gutmann Japan
Jonathan Kelly Canada
Joel A. Hesch United States
Cédric Demonceaux France
Fridtjof Stein Germany
Ivan Dryanovski United States
Paulo Borges Australia
Matthew Koichi Grimes relative to Jürgen Hess Germany Jürgen Hess's profile →
Citations per field
00.5×4.9×
Jürgen Hess · 1×
Citations per year

Countries citing papers authored by Matthew Koichi Grimes

Since Specialization
Citations

This map shows the geographic impact of Matthew Koichi Grimes's research. 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 Matthew Koichi Grimes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Koichi Grimes more than expected).

Fields of papers citing papers by Matthew Koichi Grimes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew Koichi Grimes. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matthew Koichi Grimes. The network helps show where Matthew Koichi Grimes may publish in the future.

Co-authorship network of co-authors of Matthew Koichi Grimes

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Koichi Grimes. A scholar is included among the top collaborators of Matthew Koichi Grimes based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthew Koichi Grimes. Matthew Koichi Grimes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

3 of 3 papers shown
#WorkIndexed citations
1
Convolutional networks for real-time 6-DOF camera relocalization.
31
2
PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalizationbreakdown →
1356
3 5

About Matthew Koichi Grimes

Matthew Koichi Grimes is a scholar working on Computer Graphics and Computer-Aided Design, Aerospace Engineering and Computer Vision and Pattern Recognition, having authored 3 papers that have together received 1.4k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (3 papers), Advanced Vision and Imaging (2 papers) and Advanced Image and Video Retrieval Techniques (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.1k citations), Aerospace Engineering (1.0k citations) and Geology (218 citations). Matthew Koichi Grimes has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Alex Kendall, Roberto Cipolla, Dragomir Anguelov and Yann LeCun. Their work appears in journals such as arXiv (Cornell University).

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.

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