Adrian G. Borş
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 2%
- Computer Graphics and Computer-Aided Design top 1%
- Signal Processing top 5%
- Computational Mechanics top 10%
- Co-authors
- Ioannis PitasFei YeMing LuoMoncef GabboujVassilios ChatzisThomas J. HarteEdwin R. HancockWilliam Puech
- Topics
- Computer Graphics and Visualization Techniques (28 papers)Advanced Steganography and Watermarking Techniques (27 papers)Advanced Vision and Imaging (24 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionSignal Processing
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsIEEE Transactions on Image Processing
- Partner nations
- United KingdomGreeceFrance
In The Last Decade
Adrian G. Borş
118 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 126
- Computer Vision and Pattern Recognition 1.2k
- Artificial Intelligence 522
- Computer Graphics and Computer-Aided Design 280
- Signal Processing 239
- Computational Mechanics 112
Countries citing papers authored by Adrian G. Borş
This map shows the geographic impact of Adrian G. Borş'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 G. Borş with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrian G. Borş more than expected).
Fields of papers citing papers by Adrian G. Borş
This network shows the impact of papers produced by Adrian G. Borş. 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 G. Borş. The network helps show where Adrian G. Borş may publish in the future.
Co-authorship network of co-authors of Adrian G. Borş
This figure shows the co-authorship network connecting the top 25 collaborators of Adrian G. Borş. A scholar is included among the top collaborators of Adrian G. Borş 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 G. Borş. Adrian G. Borş is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 4 | |
| 7 | 8 | |
| 8 | 7 | |
| 9 | 2 | |
| 10 | 7 | |
| 11 | 10 | |
| 12 | 49 | |
| 13 | 43 | |
| 14 | 104 | |
| 15 | 10 | |
| 16 | 5 | |
| 17 | 5 | |
| 18 | 2 | |
| 19 | 27 | |
| 20 | 57 |
About Adrian G. Borş
Adrian G. Borş is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 130 papers that have together received 1.8k indexed citations. Recurring topics across this work include Computer Graphics and Visualization Techniques (28 papers), Advanced Steganography and Watermarking Techniques (27 papers) and Advanced Vision and Imaging (24 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (280 citations), Computer Vision and Pattern Recognition (1.2k citations) and Signal Processing (239 citations). Adrian G. Borş has collaborated with scholars based in United Kingdom, Greece and France. Frequent co-authors include Ioannis Pitas, Fei Ye, Ming Luo, Moncef Gabbouj, Vassilios Chatzis, Thomas J. Harte, Edwin R. Hancock, William Puech, Richard C. Wilson and Richard Wilson. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Transactions on Image Processing.
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.