Tunç Aşuroğlu

964 total citations
47 papers, 475 citations indexed

About

Tunç Aşuroğlu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Tunç Aşuroğlu has authored 47 papers receiving a total of 475 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 8 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Tunç Aşuroğlu's work include Machine Learning in Healthcare (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Hydrological Forecasting Using AI (3 papers). Tunç Aşuroğlu is often cited by papers focused on Machine Learning in Healthcare (5 papers), Radiomics and Machine Learning in Medical Imaging (4 papers) and Hydrological Forecasting Using AI (3 papers). Tunç Aşuroğlu collaborates with scholars based in Türkiye, Finland and Norway. Tunç Aşuroğlu's co-authors include Koray Açıcı, Hasan Oğul, Mehmet Serdar Güzel, Erkan Bostancı, Çağatay Berke Erdaş, Hamit Erdem, M. Kılınç Toprak, Ricardo Colomo‐Palacios, Alejandro Baldominos and Engin Koçak and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Tunç Aşuroğlu

42 papers receiving 458 citations

Peers

Tunç Aşuroğlu

CVPR

NEURO

RNMI

Koray Açıcı Türkiye

Olivier Pauly Germany

Haseeb Hassan China

Tassilo Klein Germany

Paweł Badura Poland

Muhammad Nadeem Pakistan

D. R. Sarvamangala India

Gurpreet Singh India

Nandhini Santhanam Germany

Simone Balocco Spain

Koray Açıcı Türkiye

Tunç Aşuroğlu

81 ×0.8

118 ×1.2

104 ×1.4

CVPR

45 ×0.7

NEURO

42 ×0.8

RNMI

Citations per year, relative to Tunç Aşuroğlu Tunç Aşuroğlu (= 1×) peers Koray Açıcı

Countries citing papers authored by Tunç Aşuroğlu

Since Specialization

Citations

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

Fields of papers citing papers by Tunç Aşuroğlu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tunç Aşuroğlu

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

All Works

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20 of 20 papers shown

Güzel, Mehmet Serdar, et al.. (2025). Advanced deep learning approaches for the automated classification of macrofungal species in biodiversity monitoring. SHILAP Revista de lepidopterología.

Aşuroğlu, Tunç, et al.. (2025). A comparative feature selection study: Predicting Alzheimer's disease using primary healthcare and social services data. Informatics in Medicine Unlocked. 59. 101703–101703.

Açıcı, Koray, et al.. (2025). Classification of Mycena and Marasmius Species Using Deep Learning Models: An Ecological and Taxonomic Approach. Sensors. 25(6). 1642–1642. 6 indexed citations

Güzel, Mehmet Serdar, et al.. (2024). Comparative Analysis of Deep Learning Methods on CT Images for Lung Cancer Specification. Cancers. 16(19). 3321–3321. 2 indexed citations

Büyüksungur, Arda, et al.. (2024). Comparison of X-Ray Absorption in Mandibular Tissues and Tissue-Equivalent Polymeric Materials Using PHITS Monte Carlo Simulations. Applied Sciences. 14(23). 10879–10879. 1 indexed citations

Aşuroğlu, Tunç, et al.. (2024). Voice Analysis in Dogs with Deep Learning: Development of a Fully Automatic Voice Analysis System for Bioacoustics Studies. Sensors. 24(24). 7978–7978. 2 indexed citations

Wali, Aamir, et al.. (2024). Psychiatric disorders from EEG signals through deep learning models. IBRO Neuroscience Reports. 17. 300–310. 3 indexed citations

Aşuroğlu, Tunç. (2024). Enhancing precision in proton therapy: Utilizing machine learning for predicting Bragg curve peak location in cancer treatment. DergiPark (Istanbul University). 66(2). 140–161. 1 indexed citations

Shahid, Saman, et al.. (2024). Computational imaging for rapid detection of grade-I cerebral small vessel disease (cSVD). Heliyon. 10(18). e37743–e37743. 7 indexed citations

10.

Bostancı, Erkan, et al.. (2023). Semantic Segmentation with High-Resolution Sentinel-1 SAR Data. Applied Sciences. 13(10). 6025–6025. 2 indexed citations

11.

Güzel, Mehmet Serdar, et al.. (2023). Deep-Learning-Based Approaches for Semantic Segmentation of Natural Scene Images: A Review. Electronics. 12(12). 2730–2730. 54 indexed citations

12.

Güzel, Mehmet Serdar, et al.. (2023). Multilabel Genre Prediction Using Deep-Learning Frameworks. Applied Sciences. 13(15). 8665–8665. 8 indexed citations

13.

Kamburoğlu, Kıvanç, et al.. (2023). Interpretation of Magnetic Resonance Images of Temporomandibular Joint Disorders by Using Deep Learning. IEEE Access. 11. 49102–49113. 12 indexed citations

14.

Aşuroğlu, Tunç, et al.. (2023). Mortality Prediction of Various Cancer Patients via Relevant Feature Analysis and Machine Learning. SN Computer Science. 4(3). 7 indexed citations

15.

Bostancı, Erkan, et al.. (2023). Machine Learning Analysis of RNA-seq Data for Diagnostic and Prognostic Prediction of Colon Cancer. Sensors. 23(6). 3080–3080. 18 indexed citations

16.

Aşuroğlu, Tunç, et al.. (2023). Monte Carlo Simulation of TRIM Algorithm in Ceramic Biomaterial in Proton Therapy. Materials. 16(13). 4833–4833. 7 indexed citations

17.

Bostancı, Erkan, et al.. (2023). A New Approach for Gastrointestinal Tract Findings Detection and Classification: Deep Learning-Based Hybrid Stacking Ensemble Models. Diagnostics. 13(4). 720–720. 25 indexed citations

18.

Açıcı, Koray, et al.. (2023). MC TRIM Algorithm in Mandibula Phantom in Helium Therapy. Healthcare. 11(18). 2523–2523. 4 indexed citations

19.

Bostancı, Erkan, et al.. (2023). Deep Learning in Diagnosis of Dental Anomalies and Diseases: A Systematic Review. Diagnostics. 13(15). 2512–2512. 30 indexed citations

20.

Aşuroğlu, Tunç & Hasan Oğul. (2020). A deep learning approach for sepsis monitoring via severity score estimation. Computer Methods and Programs in Biomedicine. 198. 105816–105816. 33 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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