Serhan Coşar

795 citations
20 papers · 500 · h-index 10

Impact in

Papers in

Serhan Coşar

19 papers receiving 488 citations

Peers

Serhan Coşar
Comparison fields: 5 of 70
  • Computer Vision and Pattern Recognition 273
  • Automotive Engineering 102
  • Safety, Risk, Reliability and Quality 76
  • Artificial Intelligence 188
  • Social Psychology 95
Replace Ha Manh with:
Ha Manh United States
Luis Unzueta Spain
Christian Dondrup United Kingdom
Garratt Gallagher United States
Julien Bruneau France
Ji Hyun Yang South Korea
Rongrong Ni China
Tareq Alhmiedat Saudi Arabia
Qi Deng Germany
Photchara Ratsamee Japan
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Citations per field
00.5×2.8×
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Citations per year

Countries citing papers authored by Serhan Coşar

Since Specialization
Citations

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

Fields of papers citing papers by Serhan Coşar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Serhan Coşar, 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 Serhan Coşar Line = papers co-authored together Serhan Coşar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2016134
2 202094
3 202093
4 202052
5 201819
6 201717
7 201913
8 201911
9 201710
10 201010
11 20159
12 20188
13 20148
14 20177
15
ENRICHME integration of ambient intelligence and robotics for AAL
20175
16 20114
17 20103
18 20172
19 20151
20 20250

About Serhan Coşar

Serhan Coşar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Automotive Engineering, Biomedical Engineering and Computer Networks and Communications, having authored 20 papers that have together received 500 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (10 papers), Human Pose and Action Recognition (7 papers), Context-Aware Activity Recognition Systems (6 papers), Anomaly Detection Techniques and Applications (5 papers), Autonomous Vehicle Technology and Safety (3 papers), Gait Recognition and Analysis (2 papers), IoT and Edge/Fog Computing (2 papers) and Evacuation and Crowd Dynamics (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (273 citations), Automotive Engineering (102 citations), Safety, Risk, Reliability and Quality (76 citations), Artificial Intelligence (188 citations) and Social Psychology (95 citations). Serhan Coşar has collaborated with scholars based in United Kingdom, France and Türkiye. Frequent co-authors include Nicola Bellotto, François Brémond, Luís Otávio Álvares, Vânia Bogorny, Fanta Camara, Feng Zhao, Shigang Yue, Charles Fox, Manuel F. Fernández and Müjdat Çetin. Their work appears in journals such as IEEE Transactions on Intelligent Transportation Systems, International Journal of Social Robotics, Sensors, Image and Vision Computing and Journal of Intelligent & Robotic Systems.

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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