Berkan Solmaz

657 citations
16 papers · 388 · h-index 9

Impact in

Papers in

Berkan Solmaz

16 papers receiving 373 citations

Peers

Berkan Solmaz
Comparison fields: 5 of 60
  • Computer Vision and Pattern Recognition 308
  • Artificial Intelligence 201
  • Ocean Engineering 81
  • Safety, Risk, Reliability and Quality 25
  • Human-Computer Interaction 11
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Mani Ranjbar Canada
Seokeon Choi South Korea
Guangcong Wang China
Chuchu Han China
Nima Razavi Switzerland
Guile Wu United Kingdom
Lijie Fan United States
Mengshi Qi China
Berkan Solmaz relative to Mani Ranjbar Canada Mani Ranjbar's profile →
Citations per field
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Citations per year

Countries citing papers authored by Berkan Solmaz

Since Specialization
Citations

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

Fields of papers citing papers by Berkan Solmaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Berkan Solmaz, 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 Berkan Solmaz Line = papers co-authored together Berkan Solmaz links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2012178
2 201269
3 201633
4 201219
5 201217
6 201216
7 202015
8 201811
9 20179
10 20177
11 20173
12 20183
13 20183
14 20172
15 20172
16 20201

About Berkan Solmaz

Berkan Solmaz is a scholar working on Computer Vision and Pattern Recognition, Ocean Engineering, Media Technology, Artificial Intelligence and Aerospace Engineering, having authored 16 papers that have together received 388 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Video Surveillance and Tracking Methods (5 papers), Advanced Neural Network Applications (4 papers), Maritime Navigation and Safety (3 papers), Remote-Sensing Image Classification (2 papers), Human Pose and Action Recognition (2 papers), Infrared Target Detection Methodologies (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (308 citations), Artificial Intelligence (201 citations), Ocean Engineering (81 citations), Safety, Risk, Reliability and Quality (25 citations) and Human-Computer Interaction (11 citations). Berkan Solmaz has collaborated with scholars based in Türkiye, United States and Switzerland. Frequent co-authors include Mubarak Shah, Brian E. Moore, Aykut Koç, Erhan Gündoğdu, A. Aydın Alatan, Riad Hammoud, A. Ravishankar Rao, Nicholas G. Avgeropoulos, K. Krishna Reddy and Pingkun Yan. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Applied Optics, International Journal of Computer Vision, Machine Vision and Applications and Abdominal Radiology.

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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