Ilker Ersoy

1.4k total citations
43 papers, 897 citations indexed

About

Ilker Ersoy is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biophysics. According to data from OpenAlex, Ilker Ersoy has authored 43 papers receiving a total of 897 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 13 papers in Artificial Intelligence and 12 papers in Biophysics. Recurrent topics in Ilker Ersoy's work include Cell Image Analysis Techniques (12 papers), Digital Imaging for Blood Diseases (7 papers) and AI in cancer detection (7 papers). Ilker Ersoy is often cited by papers focused on Cell Image Analysis Techniques (12 papers), Digital Imaging for Blood Diseases (7 papers) and AI in cancer detection (7 papers). Ilker Ersoy collaborates with scholars based in United States, Türkiye and Thailand. Ilker Ersoy's co-authors include Kannappan Palaniappan, Filiz Bunyak, Stefan Jaeger, Richard J. Maude, George R. Thoma, Mahdieh Poostchi, Kamolrat Silamut, Guna Seetharaman, Andrew J. Powell and Peng Guo and has published in prestigious journals such as The Journal of Physiology, Free Radical Biology and Medicine and BMC Bioinformatics.

In The Last Decade

Ilker Ersoy

41 papers receiving 874 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ilker Ersoy United States 16 502 200 183 129 121 43 897
Ida‐Maria Sintorn Sweden 15 294 0.6× 161 0.8× 320 1.7× 92 0.7× 266 2.2× 46 981
Jesús Salido Spain 13 477 1.0× 166 0.8× 112 0.6× 58 0.4× 64 0.5× 30 863
Flávio H. D. Araújo Brazil 18 499 1.0× 513 2.6× 103 0.6× 444 3.4× 31 0.3× 59 1.0k
Faliu Yi South Korea 17 347 0.7× 166 0.8× 202 1.1× 117 0.9× 38 0.3× 42 850
Guillermo Ayala Spain 17 257 0.5× 71 0.4× 64 0.3× 132 1.0× 291 2.4× 79 1.1k
Mirabela Rusu United States 20 211 0.4× 290 1.4× 144 0.8× 516 4.0× 173 1.4× 84 1.2k
John H. Phan United States 21 257 0.5× 465 2.3× 185 1.0× 255 2.0× 712 5.9× 68 1.7k
Zhi Lü China 17 238 0.5× 124 0.6× 218 1.2× 166 1.3× 576 4.8× 49 1.4k
Frank Kulwa China 11 212 0.4× 451 2.3× 107 0.6× 338 2.6× 28 0.2× 25 765

Countries citing papers authored by Ilker Ersoy

Since Specialization
Citations

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

Fields of papers citing papers by Ilker Ersoy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ilker Ersoy

This figure shows the co-authorship network connecting the top 25 collaborators of Ilker Ersoy. A scholar is included among the top collaborators of Ilker Ersoy 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 Ilker Ersoy. Ilker Ersoy 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.
Haithcoat, Timothy L., et al.. (2024). Land Valuation Using an Innovative Model Combining Machine Learning and Spatial Context. MOspace Institutional Repository (University of Missouri). 83. 4688–4692.
2.
3.
Ersoy, Ilker, et al.. (2021). DRPnet: automated particle picking in cryo-electron micrographs using deep regression. BMC Bioinformatics. 22(1). 55–55. 16 indexed citations
4.
Yang, Feng, Sivaramakrishnan Rajaraman, Ilker Ersoy, et al.. (2020). Malaria Screener: a smartphone application for automated malaria screening. BMC Infectious Diseases. 20(1). 825–825. 39 indexed citations
5.
Öztel, İsmail, Gözde Yolcu, Ilker Ersoy, Tommi White, & Filiz Bunyak. (2018). Deep learning approaches in electron microscopy imaging for mitochondria segmentation. International Journal of Data Mining and Bioinformatics. 21(2). 91–91. 7 indexed citations
6.
Ersoy, Ilker, et al.. (2018). REDESIGN: RDF-based Differential Signaling Framework for Precision Medicine Analytics.. PubMed. 2017. 35–44. 1 indexed citations
7.
Rajaraman, Sivaramakrishnan, Kamolrat Silamut, Md. Aiub Hossain, et al.. (2018). Understanding the learned behavior of customized convolutional neural networks toward malaria parasite detection in thin blood smear images. Journal of Medical Imaging. 5(3). 1–1. 43 indexed citations
8.
Jaeger, Stefan, K Silamut, Hang Yu, et al.. (2017). REDUCING THE DIAGNOSTIC BURDEN OF MALARIA USING MICROSCOPY IMAGE ANALYSIS AND MACHINE LEARNING IN THE FIELD. American Journal of Tropical Medicine and Hygiene. 95. 475–475. 1 indexed citations
9.
Ersoy, Ilker, et al.. (2017). PathEdEx – Uncovering High-explanatory Visual Diagnostics Heuristics Using Digital Pathology and Multiscale Gaze Data. Journal of Pathology Informatics. 8(1). 29–29. 6 indexed citations
10.
Ersoy, Ilker, et al.. (2017). Integrating segmentation with deep learning for enhanced classification of epithelial and stromal tissues in H&E images. Pattern Recognition Letters. 119. 214–221. 43 indexed citations
11.
Kwon, Jaeyul, Aibing Wang, Howard E. Boudreau, et al.. (2016). Peroxiredoxin 6 (Prdx6) supports NADPH oxidase1 (Nox1)-based superoxide generation and cell migration. Free Radical Biology and Medicine. 96. 99–115. 44 indexed citations
12.
Czajkowski, Robert, Anthony J. Ries, Patricia L. McDermott, et al.. (2015). A Scalable Architecture for Operational FMV Exploitation. 78. 1062–1070. 3 indexed citations
13.
Hong, Zhongkui, Zhe Sun, Min Li, et al.. (2014). Vasoactive agonists exert dynamic and coordinated effects on vascular smooth muscle cell elasticity, cytoskeletal remodelling and adhesion. The Journal of Physiology. 592(6). 1249–1266. 45 indexed citations
14.
Hong, Zhongkui, Ilker Ersoy, Mingzhai Sun, et al.. (2012). Influence of membrane cholesterol and substrate elasticity on endothelial cell spreading behavior. Journal of Biomedical Materials Research Part A. 101A(7). 1994–2004. 7 indexed citations
15.
Palaniappan, Kannappan, Ilker Ersoy, Guna Seetharaman, et al.. (2011). Parallel flux tensor analysis for efficient moving object detection. International Conference on Information Fusion. 1–8. 13 indexed citations
16.
Mosig, Axel, Stefan Jäger, Chaofeng Wang, et al.. (2009). Tracking cells in Life Cell Imaging videos using topological alignments. Algorithms for Molecular Biology. 4(1). 10–10. 30 indexed citations
17.
Ersoy, Ilker, et al.. (2008). Cell Spreading Analysis with Directed Edge Profile-Guided Level Set Active Contours. Lecture notes in computer science. 11(Pt 1). 376–383. 15 indexed citations
18.
Ersoy, Ilker, Filiz Bunyak, Michael A. Mackey, & Kannappan Palaniappan. (2008). Cell segmentation using Hessian-based detection and contour evolution with directional derivatives. PubMed. 2008. 1804–1807. 33 indexed citations
19.
Ersoy, Ilker, et al.. (2003). Evolving neural networks applied to predator-evader problem. 4. 2394–2397. 1 indexed citations
20.
Ersoy, Ilker, Fikret Erçal, & Muhittin Gökmen. (1999). A model-based approach for compression of fingerprint images. Istanbul Technical University Academic Open Archive (Istanbul Technical University). e80 a. 973–977 vol.2. 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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