Balázs Harangi
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Oncology top 10%
- Ophthalmology top 2%
- Co-authors
- András HajdúÁgnes BaranJános TóthLászló KovácsTünde PetőBrigitta NagyIstván LázárBálint Antal
- Topics
- Retinal Imaging and Analysis (17 papers)Digital Imaging for Blood Diseases (12 papers)AI in cancer detection (12 papers)
- Cited by
- OphthalmologyRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Partner nations
- HungaryUnited KingdomIraq
In The Last Decade
Balázs Harangi
50 papers receiving 906 citations
Hit Papers
Peers
Comparison fields: 5 of 93
- Radiology, Nuclear Medicine and Imaging 469
- Artificial Intelligence 367
- Computer Vision and Pattern Recognition 331
- Oncology 320
- Ophthalmology 301
Countries citing papers authored by Balázs Harangi
This map shows the geographic impact of Balázs Harangi'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 Balázs Harangi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Balázs Harangi more than expected).
Fields of papers citing papers by Balázs Harangi
This network shows the impact of papers produced by Balázs Harangi. 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 Balázs Harangi. The network helps show where Balázs Harangi may publish in the future.
Co-authorship network of co-authors of Balázs Harangi
This figure shows the co-authorship network connecting the top 25 collaborators of Balázs Harangi. A scholar is included among the top collaborators of Balázs Harangi 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 Balázs Harangi. Balázs Harangi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 5 | |
| 3 | 7 | |
| 4 | 28 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 3 | |
| 8 | 4 | |
| 9 | 10 | |
| 10 | 2 | |
| 11 | 1 | |
| 12 | 54 | |
| 13 | 17 | |
| 14 | 6 | |
| 15 | Skin lesion classification with ensembles of deep convolutional neural networksbreakdown → | 299 |
| 16 | 1 | |
| 17 | 23 | |
| 18 | 62 | |
| 19 | 28 | |
| 20 | Ensemble-based exudate detection in color fundus images | 9 |
About Balázs Harangi
Balázs Harangi is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 51 papers that have together received 948 indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (17 papers), Digital Imaging for Blood Diseases (12 papers) and AI in cancer detection (12 papers). The work is most often cited by research in Ophthalmology (301 citations), Radiology, Nuclear Medicine and Imaging (469 citations) and Computer Vision and Pattern Recognition (331 citations). Balázs Harangi has collaborated with scholars based in Hungary, United Kingdom and Iraq. Frequent co-authors include András Hajdú, Ágnes Baran, János Tóth, László Kovács, Tünde Pető, Brigitta Nagy, István Lázár, Bálint Antal, Péter Török and Mohammed A. Fadhel. Their work appears in journals such as SHILAP Revista de lepidopterología, Sensors and Materials.
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.