Serhan Coşar

795 total citations
20 papers, 500 citations indexed

About

Serhan Coşar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Automotive Engineering. According to data from OpenAlex, Serhan Coşar has authored 20 papers receiving a total of 500 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 5 papers in Artificial Intelligence and 3 papers in Automotive Engineering. Recurrent topics in Serhan Coşar's work include Video Surveillance and Tracking Methods (10 papers), Human Pose and Action Recognition (7 papers) and Context-Aware Activity Recognition Systems (6 papers). Serhan Coşar is often cited by papers focused on Video Surveillance and Tracking Methods (10 papers), Human Pose and Action Recognition (7 papers) and Context-Aware Activity Recognition Systems (6 papers). Serhan Coşar collaborates with scholars based in United Kingdom, France and Türkiye. Serhan Coşar's co-authors include Nicola Bellotto, François Brémond, Vânia Bogorny, Luís Otávio Álvares, Charles Fox, Fanta Camara, Shigang Yue, Feng Zhao, Manuel F. Fernández and Müjdat Çetin and has published in prestigious journals such as Sensors, IEEE Transactions on Intelligent Transportation Systems and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Serhan Coşar

19 papers receiving 488 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Serhan Coşar United Kingdom 10 273 188 102 95 76 20 500
Ha Manh United States 13 194 0.7× 82 0.4× 65 0.6× 124 1.3× 27 0.4× 18 482
Garratt Gallagher United States 4 300 1.1× 174 0.9× 109 1.1× 85 0.9× 39 0.5× 6 537
Luis Unzueta Spain 10 247 0.9× 44 0.2× 41 0.4× 19 0.2× 17 0.2× 35 389
Peter Trautman United States 6 336 1.2× 184 1.0× 258 2.5× 116 1.2× 48 0.6× 9 595
Photchara Ratsamee Japan 13 198 0.7× 58 0.3× 30 0.3× 136 1.4× 16 0.2× 51 434
Rongrong Ni China 13 275 1.0× 102 0.5× 123 1.2× 24 0.3× 40 0.5× 35 521
Keshav Chintamani United States 7 115 0.4× 44 0.2× 23 0.2× 98 1.0× 23 0.3× 14 443
Christian Dondrup United Kingdom 10 151 0.6× 153 0.8× 23 0.2× 163 1.7× 7 0.1× 40 355
Renran Tian United States 12 110 0.4× 58 0.3× 169 1.7× 82 0.9× 117 1.5× 43 365
Andrew Best United States 13 195 0.7× 76 0.4× 136 1.3× 76 0.8× 54 0.7× 34 489

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-authorship network of co-authors of Serhan Coşar

This figure shows the co-authorship network connecting the top 25 collaborators of Serhan Coşar. A scholar is included among the top collaborators of Serhan Coşar 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 Serhan Coşar. Serhan Coşar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Camara, Fanta, Nicola Bellotto, Serhan Coşar, et al.. (2020). Pedestrian Models for Autonomous Driving Part II: High-Level Models of Human Behavior. IEEE Transactions on Intelligent Transportation Systems. 22(9). 5453–5472. 94 indexed citations
3.
Camara, Fanta, Nicola Bellotto, Serhan Coşar, et al.. (2020). Pedestrian Models for Autonomous Driving Part I: Low-Level Models, From Sensing to Tracking. IEEE Transactions on Intelligent Transportation Systems. 22(10). 6131–6151. 52 indexed citations
4.
Coşar, Serhan, Manuel F. Fernández, Jordi F. Pagès, et al.. (2020). ENRICHME: Perception and Interaction of an Assistive Robot for the Elderly at Home. International Journal of Social Robotics. 12(3). 779–805. 93 indexed citations
5.
Coşar, Serhan & Nicola Bellotto. (2019). Human Re-Identification with a Robot Thermal Camera Using Entropy-Based Sampling. Journal of Intelligent & Robotic Systems. 98(1). 85–102. 11 indexed citations
6.
Coşar, Serhan, et al.. (2019). Social Activity Recognition on Continuous RGB-D Video Sequences. International Journal of Social Robotics. 12(1). 201–215. 13 indexed citations
7.
Camara, Fanta, Serhan Coşar, Nicola Bellotto, Natasha Merat, & Charles Fox. (2018). Towards pedestrian-AV interaction: method for elucidating pedestrian preferences. Lincoln Repository (University of Lincoln). 8 indexed citations
8.
Coşar, Serhan, Zifei Yan, Feng Zhao, et al.. (2018). Thermal Camera Based Physiological Monitoring with an Assistive Robot. PubMed. 2018. 5010–5013. 19 indexed citations
9.
Bellotto, Nicola, Manuel F. Fernández, & Serhan Coşar. (2017). ENRICHME integration of ambient intelligence and robotics for AAL. Lincoln Repository (University of Lincoln). 5 indexed citations
10.
Coşar, Serhan, et al.. (2017). Automatic detection of human interactions from RGB-D data for social activity classification. Lincoln Repository (University of Lincoln). 871–876. 17 indexed citations
11.
Fernández, Manuel F., et al.. (2017). Entropy-based abnormal activity detection fusing RGB-D and domotic sensors. Lincoln Repository (University of Lincoln). 2. 42–48. 2 indexed citations
12.
Coşar, Serhan, et al.. (2017). Volume-based Human Re-identification with RGB-D Cameras. Research Padua Archive (University of Padua). 389–397. 7 indexed citations
13.
Crispim-Junior, Carlos, et al.. (2017). Online Recognition of Daily Activities by Color-Depth Sensing and Knowledge Models. Sensors. 17(7). 1528–1528. 10 indexed citations
14.
Coşar, Serhan, et al.. (2016). Toward Abnormal Trajectory and Event Detection in Video Surveillance. IEEE Transactions on Circuits and Systems for Video Technology. 27(3). 683–695. 134 indexed citations
15.
Coşar, Serhan & Müjdat Çetin. (2015). Sparsity-driven bandwidth-efficient decentralized tracking in visual sensor networks. Computer Vision and Image Understanding. 139. 40–58. 1 indexed citations
16.
Coşar, Serhan, et al.. (2015). Unsupervised discovery of human activities from long‐time videos. IET Computer Vision. 9(4). 522–530. 9 indexed citations
17.
Coşar, Serhan & Müjdat Çetin. (2014). Feature compression: A framework for multi-view multi-person tracking in visual sensor networks. Journal of Visual Communication and Image Representation. 25(5). 864–873. 8 indexed citations
18.
Coşar, Serhan & Müjdat Çetin. (2011). A group sparsity-driven approach to 3-D action recognition. 4. 1904–1911. 4 indexed citations
19.
Coşar, Serhan & Müjdat Çetin. (2010). A graphical model based solution to the facial feature point tracking problem. Image and Vision Computing. 29(5). 335–350. 10 indexed citations
20.
Coşar, Serhan, et al.. (2010). Air drums: A computer vision based drums simulator. 844–847. 3 indexed citations

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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