John McCormac

1.7k citations
3 papers · 791 · 1 hit paper · h-index 3

Impact in

  • Geology top 2%
    • 3D Surveying and Cultural Heritage
    • Advanced Image and Video Retrieval Techniques
    • Advanced Vision and Imaging
    • Robotic Path Planning Algorithms
    • Advanced Neural Network Applications

Papers in

John McCormac

3 papers receiving 759 citations

John McCormac's Hit Papers

SemanticFusion: Dense 3D semantic mapping with convolutional neural networks 2017 · 431 citations
4310+3+6Years since publication100200300400

Peers

John McCormac
Comparison fields: 5 of 46
  • Geology 221
  • Computer Vision and Pattern Recognition 622
  • Aerospace Engineering 549
  • Environmental Engineering 82
  • Computer Graphics and Computer-Aided Design 19
Replace Aitor Aldomà with:
Aitor Aldomà Austria
Haoang Li Hong Kong
Dániel Baráth Switzerland
Jingnan Shi United States
Enrique Dunn United States
Bertram Drost Germany
Manuel Werlberger Austria
Pedro Miraldo Portugal
Narunas Vaškevičius Germany
Keisuke Tateno United States
John McCormac relative to Aitor Aldomà Austria Aitor Aldomà's profile →
Citations per field
00.5×5.2×
Aitor Aldomà · 1×
Citations per year

Countries citing papers authored by John McCormac

Since Specialization
Citations

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

Fields of papers citing papers by John McCormac

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John McCormac. 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 John McCormac. The network helps show where John McCormac may publish in the future.

Co-authors

The 5 scholars most cited alongside John McCormac, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John McCormac Line = papers co-authored together John McCormac links everyone, so they are left out of the graph.

All Works

3 of 3 papers shown
#Work
1
SemanticFusion: Dense 3D semantic mapping with convolutional neural networks
Hit paper breakdown →
2017431
2 2018200
3 2017160

About John McCormac

John McCormac is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Geology, Infectious Diseases and Organic Chemistry, having authored 3 papers that have together received 791 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Neural Network Applications (1 paper), Advanced Vision and Imaging (1 paper) and 3D Surveying and Cultural Heritage (1 paper). The work is most often cited by research in Geology (221 citations), Computer Vision and Pattern Recognition (622 citations), Aerospace Engineering (549 citations), Environmental Engineering (82 citations) and Computer Graphics and Computer-Aided Design (19 citations). John McCormac has collaborated with scholars based in United Kingdom. Frequent co-authors include Andrew J. Davison, Stefan Leutenegger, Ankur Handa, Michael Bloesch and Ronald Clark. Their work appears in journals such as Spiral (Imperial College London).

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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