Ertunç Erdil

1.1k citations
26 papers · 471 · 1 hit paper · h-index 10

Impact in

Papers in

Ertunç Erdil

25 papers receiving 458 citations

Ertunç Erdil's Hit Papers

Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation 2023 · 133 citations
1330+1+2Years since publication4080120

Peers

Ertunç Erdil
Comparison fields: 5 of 81
  • Computer Vision and Pattern Recognition 259
  • Biophysics 42
  • Artificial Intelligence 224
  • Radiology, Nuclear Medicine and Imaging 116
  • Neurology 42
Replace Neelam Sinha with:
Neelam Sinha India
Hidekata Hontani Japan
Firdaus Janoos United States
Hatice Çınar Akakın Türkiye
Nadia Brancati Italy
Shunren Xia China
Giovanni Danese Italy
Mahdieh Soleymani Baghshah Iran
Jundong Liu United States
Ertunç Erdil relative to Neelam Sinha India Neelam Sinha's profile →
Citations per field
00.5×2×3×3.5×
Neelam Sinha · 1×
Citations per year

Countries citing papers authored by Ertunç Erdil

Since Specialization
Citations

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

Fields of papers citing papers by Ertunç Erdil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ertunç Erdil, 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 Ertunç Erdil Line = papers co-authored together Ertunç Erdil links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation
Hit paper breakdown →
2023133
2 2020128
3 201068
4 201715
5 201315
6 202213
7 201711
8 201611
9 20159
10 20169
11 20107
12 20187
13 20147
14 20117
15 20126
16 20235
17 20195
18 20175
19
Unsupervised out-of-distribution detection using kernel density estimation
20203
20 20172

About Ertunç Erdil

Ertunç Erdil is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Biophysics and Cellular and Molecular Neuroscience, having authored 26 papers that have together received 471 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (11 papers), Image Processing Techniques and Applications (7 papers), Cell Image Analysis Techniques (6 papers), Image Retrieval and Classification Techniques (5 papers), Neuroscience and Neuropharmacology Research (4 papers), Domain Adaptation and Few-Shot Learning (4 papers), Advanced Neural Network Applications (3 papers) and Advanced Clustering Algorithms Research (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (259 citations), Biophysics (42 citations), Artificial Intelligence (224 citations), Radiology, Nuclear Medicine and Imaging (116 citations) and Neurology (42 citations). Ertunç Erdil has collaborated with scholars based in Türkiye, United States and Portugal. Frequent co-authors include Ender Konukoğlu, Krishna Chaitanya, Neerav Karani, Müjdat Çetin, Tolga Taşdizen, Devrim Ünay, Lavdie Rada, Inbal Israely, Bruno Weber and Theofanis Karayannis. Their work appears in journals such as Medical Image Analysis, Engineering Applications of Artificial Intelligence, IEEE Transactions on Image Processing, Bioinformatics and Pattern Recognition.

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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