Gökhan Bilgin

1.2k total citations
100 papers, 866 citations indexed

About

Gökhan Bilgin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Media Technology. According to data from OpenAlex, Gökhan Bilgin has authored 100 papers receiving a total of 866 indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Artificial Intelligence, 52 papers in Computer Vision and Pattern Recognition and 39 papers in Media Technology. Recurrent topics in Gökhan Bilgin's work include AI in cancer detection (48 papers), Remote-Sensing Image Classification (38 papers) and Digital Imaging for Blood Diseases (25 papers). Gökhan Bilgin is often cited by papers focused on AI in cancer detection (48 papers), Remote-Sensing Image Classification (38 papers) and Digital Imaging for Blood Diseases (25 papers). Gökhan Bilgin collaborates with scholars based in Türkiye, United States and Germany. Gökhan Bilgin's co-authors include Tülay Yıldırım, Sunil Badve, Metin N. Gürcan, M. Murat Dundar, Rohit Jain, Vikas C. Raykar, Olcay Sertel, Sarp Ertürk, Şükrü Mehmet Ertürk and Mustafa Üstüner and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Geoscience and Remote Sensing and IEEE Access.

In The Last Decade

Gökhan Bilgin

90 papers receiving 818 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gökhan Bilgin Türkiye 14 494 390 251 218 127 100 866
Çağlar Şenaras United States 13 213 0.4× 223 0.6× 263 1.0× 140 0.6× 101 0.8× 30 731
Emanuele Torti Italy 17 109 0.2× 160 0.4× 177 0.7× 280 1.3× 86 0.7× 67 838
Zoltán Kató Hungary 19 217 0.4× 704 1.8× 300 1.2× 53 0.2× 70 0.6× 62 1.1k
Nicolas Passat France 18 102 0.2× 772 2.0× 221 0.9× 281 1.3× 97 0.8× 80 1.2k
Volodymyr Ponomaryov Mexico 15 256 0.5× 628 1.6× 298 1.2× 129 0.6× 32 0.3× 172 1.1k
Weiying Xie China 12 171 0.3× 476 1.2× 562 2.2× 72 0.3× 128 1.0× 25 827
Nebras Ahmed Mohamed United States 5 316 0.6× 1.1k 2.8× 500 2.0× 170 0.8× 71 0.6× 9 1.4k
Jun Bai China 8 157 0.3× 224 0.6× 251 1.0× 85 0.4× 80 0.6× 25 550
M.N. Ahmed United States 6 325 0.7× 1.2k 3.0× 517 2.1× 180 0.8× 73 0.6× 10 1.5k
Jay Wu Taiwan 11 265 0.5× 683 1.8× 259 1.0× 292 1.3× 38 0.3× 31 1.2k

Countries citing papers authored by Gökhan Bilgin

Since Specialization
Citations

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

Fields of papers citing papers by Gökhan Bilgin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gökhan Bilgin

This figure shows the co-authorship network connecting the top 25 collaborators of Gökhan Bilgin. A scholar is included among the top collaborators of Gökhan Bilgin 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 Gökhan Bilgin. Gökhan Bilgin 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.
Bilgin, Gökhan, et al.. (2025). HFT-Net: Hybrid Fusion Transformer Network for Multi-Source Breast Cancer Classification. IEEE Access. 13. 170126–170146.
2.
Bilgin, Gökhan, et al.. (2025). An end-to-end active learning framework for limited labelled hyperspectral image classification. International Journal of Remote Sensing. 46(8). 3179–3206. 2 indexed citations
3.
Bilgin, Gökhan, et al.. (2024). Deep Learning Approach to Improve Breast CancerClassification for Screening Mammography. 1–4. 2 indexed citations
4.
5.
Bilgin, Gökhan, et al.. (2023). Active learning with Bayesian CNN Using the BALD Method for Hyperspectral Image Classification. 2023. 53–60. 6 indexed citations
6.
Bilgin, Gökhan, et al.. (2022). Spectral-Spatial Classification of Hyperspectral Images Using BERT-Based Methods With HyperSLIC Segment Embeddings. IEEE Access. 10. 79152–79164. 5 indexed citations
7.
Çalık, Nurullah, et al.. (2022). Classification of Cervical Precursor Lesions via Local Histogram and Cell Morphometric Features. IEEE Journal of Biomedical and Health Informatics. 27(4). 1–11. 2 indexed citations
8.
Bilgin, Gökhan, et al.. (2021). SAR image classification post-processing with multiscale complementary Gaussian kernel weighting. Signal Image and Video Processing. 15(7). 1425–1433. 1 indexed citations
9.
Çalık, Nurullah, et al.. (2021). A whole-slide image grading benchmark and tissue classification for cervical cancer precursor lesions with inter-observer variability. Medical & Biological Engineering & Computing. 59(7-8). 1545–1561. 14 indexed citations
10.
Üstüner, Mustafa, Saygın Abdikan, Gökhan Bilgin, & Füsun Balık Şanlı. (2021). Hafif Gradyan Artırma Makineleri ile Tarımsal Ürünlerin Sınıflandırılması. DergiPark (Istanbul University). 1(2). 97–105. 1 indexed citations
11.
Bilgin, Gökhan, et al.. (2021). Detection of mitotic cells in breast cancer histopathological images using deep versus handcrafted features. Multimedia Tools and Applications. 81(10). 13179–13202. 31 indexed citations
12.
Bilgin, Gökhan, et al.. (2020). Semi-supervised sparse representation classifier (S3RC) with deep features on small sample sized hyperspectral images. Neurocomputing. 399. 213–226. 8 indexed citations
13.
Bilgin, Gökhan, et al.. (2020). Classification of Breast Cancer Images Using Ensembles of Transfer Learning. SHILAP Revista de lepidopterología. 24(5). 791–802. 3 indexed citations
14.
Bilgin, Gökhan, et al.. (2019). Semisupervised Hyperspectral Image Classification Using Deep Features. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12(9). 3615–3622. 15 indexed citations
15.
Bilgin, Gökhan, et al.. (2019). MCK-ELM: multiple composite kernel extreme learning machine for hyperspectral images. Neural Computing and Applications. 32(11). 6809–6819. 15 indexed citations
16.
Bilgin, Gökhan, et al.. (2019). HCKBoost: Hybridized composite kernel boosting with extreme learning machines for hyperspectral image classification. Neurocomputing. 334. 100–113. 13 indexed citations
17.
Bilgin, Gökhan, et al.. (2018). Automatic cell segmentation in histopathological images via two-staged superpixel-based algorithms. Medical & Biological Engineering & Computing. 57(3). 653–665. 39 indexed citations
18.
Bilgin, Gökhan, et al.. (2017). Cell segmentation in histopathological images with deep learning algorithms by utilizing spatial relationships. Medical & Biological Engineering & Computing. 55(10). 1829–1848. 74 indexed citations
19.
Bilgin, Gökhan, et al.. (2017). Semisupervised Hyperspectral Image Classification Using Small Sample Sizes. IEEE Geoscience and Remote Sensing Letters. 14(5). 621–625. 36 indexed citations
20.
Bilgin, Gökhan, et al.. (2012). Exploiting locality based Fourier transform for ECG signal diagnosis. International Conference on Applied Electronics. 323–326. 5 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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