John McCormac
Impact in
- Geology top 2%
- 3D Surveying and Cultural Heritage
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- Advanced Image and Video Retrieval Techniques
- Advanced Vision and Imaging
- Robotic Path Planning Algorithms
- Advanced Neural Network Applications
Papers in
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- Advanced Image and Video Retrieval Techniques 3
- Advanced Vision and Imaging 2
- Advanced Neural Network Applications 1
- Image and Object Detection Techniques 1
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- Robotics and Sensor-Based Localization 4
- Co-authors
- Stefan Leutenegger (3 shared papers)Andrew J. Davison (3 shared papers)Ankur Handa (3 shared papers)Michael Bloesch (2 shared papers)Ronald Clark (1 shared paper)Simon Stent (1 shared paper)Viorica Pătrăucean (1 shared paper)Andrew Davison (1 shared paper)
- Journals
- Lecture notes in computer science (1 paper)Spiral (Imperial College London) (3 papers)
- Partner nations
- United KingdomSwitzerland
In The Last Decade
John McCormac
4 papers receiving 866 citations
John McCormac's Hit Papers
Peers
Comparison fields: 5 of 51
- Geology 240
- Computer Vision and Pattern Recognition 718
- Aerospace Engineering 617
- Computer Graphics and Computer-Aided Design 22
- Environmental Engineering 85
Countries citing papers authored by John McCormac
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
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 8 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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | SemanticFusion: Dense 3D semantic mapping with convolutional neural networks Hit paper breakdown → | 2017 | 455 |
| 2 | 2018 | 209 | |
| 3 | 2017 | 178 | |
| 4 | 2016 | 58 |
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 4 papers that have together received 900 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (4 papers), Advanced Image and Video Retrieval Techniques (3 papers), Advanced Vision and Imaging (2 papers), Advanced Neural Network Applications (1 paper), Image and Object Detection Techniques (1 paper) and 3D Surveying and Cultural Heritage (1 paper). The work is most often cited by research in Geology (240 citations), Computer Vision and Pattern Recognition (718 citations), Aerospace Engineering (617 citations), Computer Graphics and Computer-Aided Design (22 citations) and Environmental Engineering (85 citations). John McCormac has collaborated with scholars based in United Kingdom and Switzerland. Frequent co-authors include Stefan Leutenegger, Andrew J. Davison, Ankur Handa, Michael Bloesch, Ronald Clark, Simon Stent, Viorica Pătrăucean and Andrew Davison. Their work appears in journals such as Lecture notes in computer science and 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.