Veysel Turk

490 total citations
15 papers, 304 citations indexed

About

Veysel Turk is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Veysel Turk has authored 15 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Veysel Turk's work include AI in cancer detection (6 papers), COVID-19 diagnosis using AI (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Veysel Turk is often cited by papers focused on AI in cancer detection (6 papers), COVID-19 diagnosis using AI (4 papers) and Radiomics and Machine Learning in Medical Imaging (3 papers). Veysel Turk collaborates with scholars based in Türkiye and Australia. Veysel Turk's co-authors include Hatice Çatal Reis, Kourosh Khoshelham, Mustafa Üstüner and Ş. Karagöz and has published in prestigious journals such as Pattern Recognition, Applied Soft Computing and Neural Computing and Applications.

In The Last Decade

Veysel Turk

13 papers receiving 287 citations

Peers

Veysel Turk

ONCOL

CVPR

RNMI

G. Karuna India

S. M. Jaisakthi India

P. Mirunalini India

Muhammad Junaid Ali Pakistan

Mina Al-Saad United Arab Emirates

Emine Cengil Türkiye

Rahul Nijhawan India

Md. Mostafa Kamal Sarker United Kingdom

Andrzej Brodzicki Poland

Ulzii-Orshikh Dorj South Korea

G. Karuna India

Veysel Turk

91 ×0.8

70 ×0.7

ONCOL

18 ×0.3

25 ×0.6

CVPR

19 ×0.4

RNMI

Citations per year, relative to Veysel Turk Veysel Turk (= 1×) peers G. Karuna

Countries citing papers authored by Veysel Turk

Since Specialization

Citations

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

Fields of papers citing papers by Veysel Turk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Veysel Turk

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

All Works

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15 of 15 papers shown

Reis, Hatice Çatal, et al.. (2025). Post-seismic structural assessment: advanced crack detection through complex feature extraction using pre-trained deep learning and machine learning integration. Earth Science Informatics. 18(1). 1 indexed citations

Reis, Hatice Çatal, et al.. (2025). A deep neural network combined with a two-stage ensemble model for detecting cracks in concrete structures. Frontiers of Structural and Civil Engineering. 19(7). 1091–1109.

Reis, Hatice Çatal & Veysel Turk. (2025). A multi-stage fusion deep learning framework merging local patterns with attention-driven contextual dependencies for cancer detection. Computers in Biology and Medicine. 189. 109916–109916. 1 indexed citations

Reis, Hatice Çatal & Veysel Turk. (2024). DSCIMABNet: A novel multi-head attention depthwise separable CNN model for skin cancer detection. Pattern Recognition. 159. 111182–111182. 4 indexed citations

Reis, Hatice Çatal & Veysel Turk. (2024). Potato leaf disease detection with a novel deep learning model based on depthwise separable convolution and transformer networks. Engineering Applications of Artificial Intelligence. 133. 108307–108307. 38 indexed citations

Reis, Hatice Çatal & Veysel Turk. (2024). Fusion of transformer attention and CNN features for skin cancer detection. Applied Soft Computing. 164. 112013–112013. 24 indexed citations

Reis, Hatice Çatal, et al.. (2024). Integration of a CNN-based model and ensemble learning for detecting post-earthquake road cracks with deep features. Structures. 62. 106179–106179. 7 indexed citations

Reis, Hatice Çatal & Veysel Turk. (2024). Advanced brain tumor analysis: a novel strategy for segmentation and classification using modern computational methods. Neural Computing and Applications. 37(6). 4697–4731. 3 indexed citations

Reis, Hatice Çatal & Veysel Turk. (2023). Detection of forest fire using deep convolutional neural networks with transfer learning approach. Applied Soft Computing. 143. 110362–110362. 56 indexed citations

10.

Reis, Hatice Çatal, et al.. (2023). MediNet: transfer learning approach with MediNet medical visual database. Multimedia Tools and Applications. 82(25). 39211–39254. 8 indexed citations

11.

Reis, Hatice Çatal & Veysel Turk. (2023). Integrated deep learning and ensemble learning model for deep feature-based wheat disease detection. Microchemical Journal. 197. 109790–109790. 21 indexed citations

12.

Reis, Hatice Çatal & Veysel Turk. (2022). Transfer Learning Approach and Nucleus Segmentation with MedCLNet Colon Cancer Database. Journal of Digital Imaging. 36(1). 306–325. 20 indexed citations

13.

Reis, Hatice Çatal & Veysel Turk. (2022). COVID-DSNet: A novel deep convolutional neural network for detection of coronavirus (SARS-CoV-2) cases from CT and Chest X-Ray images. Artificial Intelligence in Medicine. 134. 102427–102427. 28 indexed citations

14.

Turk, Veysel, et al.. (2022). Derin öğrenme mimarilerini kullanarak göğüs BT görüntülerinden otomatik Covid-19 tahmini. Gümüşhane Üniversitesi Fen Bilimleri Enstitüsü Dergisi.

15.

Reis, Hatice Çatal, et al.. (2022). InSiNet: a deep convolutional approach to skin cancer detection and segmentation. Medical & Biological Engineering & Computing. 60(3). 643–662. 93 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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