Adrian J. Chung
- Computer Vision and Pattern Recognition top 5%
- Surgery
- Biomedical Engineering
- Aerospace Engineering top 10%
- Computer Graphics and Computer-Aided Design top 5%
- Co-authors
- Guang‐Zhong YangFani DeligianniMirna LeroticGeorge MylonasA. J. FieldMarios NicolaouMohamed ElhelwM. Stella Atkins
- Topics
- Robotics and Sensor-Based Localization (8 papers)3D Shape Modeling and Analysis (8 papers)Medical Image Segmentation Techniques (7 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Journals
- IEEE Transactions on Medical ImagingImage and Vision ComputingLecture notes in computer science
- Partner nations
- United KingdomCanadaTrinidad and Tobago
In The Last Decade
Adrian J. Chung
19 papers receiving 305 citations
Peers
Comparison fields: 5 of 52
- Computer Vision and Pattern Recognition 223
- Surgery 109
- Biomedical Engineering 100
- Aerospace Engineering 98
- Computer Graphics and Computer-Aided Design 51
Countries citing papers authored by Adrian J. Chung
This map shows the geographic impact of Adrian J. Chung'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 Adrian J. Chung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrian J. Chung more than expected).
Fields of papers citing papers by Adrian J. Chung
This network shows the impact of papers produced by Adrian J. Chung. 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 Adrian J. Chung. The network helps show where Adrian J. Chung may publish in the future.
Co-authorship network of co-authors of Adrian J. Chung
This figure shows the co-authorship network connecting the top 25 collaborators of Adrian J. Chung. A scholar is included among the top collaborators of Adrian J. Chung 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 Adrian J. Chung. Adrian J. Chung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 21 | |
| 3 | 33 | |
| 4 | 25 | |
| 5 | 11 | |
| 6 | 62 | |
| 7 | 1 | |
| 8 | 36 | |
| 9 | 21 | |
| 10 | 5 | |
| 11 | 13 | |
| 12 | 11 | |
| 13 | 4 | |
| 14 | 9 | |
| 15 | 3 | |
| 16 | 17 | |
| 17 | 9 | |
| 18 | 11 | |
| 19 | 17 |
About Adrian J. Chung
Adrian J. Chung is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 19 papers that have together received 321 indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (8 papers), 3D Shape Modeling and Analysis (8 papers) and Medical Image Segmentation Techniques (7 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (51 citations), Computer Vision and Pattern Recognition (223 citations) and Human-Computer Interaction (31 citations). Adrian J. Chung has collaborated with scholars based in United Kingdom, Canada and Trinidad and Tobago. Frequent co-authors include Guang‐Zhong Yang, Fani Deligianni, Mirna Lerotic, George Mylonas, A. J. Field, Marios Nicolaou, Mohamed Elhelw, M. Stella Atkins, Danail Stoyanov and Pallav L. Shah. Their work appears in journals such as IEEE Transactions on Medical Imaging, Image and Vision Computing and Lecture notes in computer science.
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.