Ahmet Çınar

70 papers receiving 1.4k citations

Ahmet Çınar's Hit Papers

Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture 2020 · 292 citations
2920+2+4Years since publication50100150200250

Peers

Ahmet Çınar
Comparison fields: 5 of 135
  • Neurology 379
  • Computer Vision and Pattern Recognition 549
  • Radiology, Nuclear Medicine and Imaging 405
  • Health Informatics 23
  • Artificial Intelligence 491
Replace Ümit Budak with:
Ümit Budak Türkiye
Abdul Qayyum Malaysia
Fatih Özyurt Türkiye
Mesut Toğaçar Türkiye
Hong Song China
Vishnuvarthanan Govindaraj India
Wei Huang China
Shivajirao M. Jadhav India
R. Karthik India
Samir S. Yadav India
Ahmet Çınar relative to Ümit Budak Türkiye Ümit Budak's profile →
Citations per field
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Ümit Budak · 1×
Citations per year

Countries citing papers authored by Ahmet Çınar

Since Specialization
Citations

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

Fields of papers citing papers by Ahmet Çınar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ahmet Çınar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ahmet Çınar Line = papers co-authored together Ahmet Çınar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 79 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture
Hit paper breakdown →
2020292
2 2021101
3 202099
4 202168
5 200258
6 201950
7 202149
8 202049
9 202146
10 202144
11 201835
12 202035
13 201934
14 201729
15 202028
16 202125
17 202125
18 202324
19 202224
20 201924

About Ahmet Çınar

Ahmet Çınar is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Plant Science and Neurology, having authored 79 papers that have together received 1.5k indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), COVID-19 diagnosis using AI (17 papers), Digital Imaging for Blood Diseases (8 papers), Advanced Neural Network Applications (8 papers), Brain Tumor Detection and Classification (8 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Smart Agriculture and AI (7 papers) and Cutaneous Melanoma Detection and Management (4 papers). The work is most often cited by research in Neurology (379 citations), Computer Vision and Pattern Recognition (549 citations), Radiology, Nuclear Medicine and Imaging (405 citations), Health Informatics (23 citations) and Artificial Intelligence (491 citations). Ahmet Çınar has collaborated with scholars based in Türkiye, Iraq and United Kingdom. Frequent co-authors include Muhammed Yıldırım, Emine Cengil, Seda Arslan Tuncer, Yeşim Eroğlu, Erdal Özbay, İbrahim Ortaş, Zülküf Kaya, Haluk Eren, Taner Tuncer and Murat Fırat. Their work appears in journals such as International Journal of Imaging Systems and Technology, TURKISH JOURNAL OF AGRICULTURE AND FORESTRY, Computers in Biology and Medicine, Applied Sciences and Journal of Ambient Intelligence and Humanized Computing.

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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