Emre Akbaş

1.3k total citations
31 papers, 277 citations indexed

About

Emre Akbaş is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Emre Akbaş has authored 31 papers receiving a total of 277 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Computer Vision and Pattern Recognition, 11 papers in Artificial Intelligence and 4 papers in Molecular Biology. Recurrent topics in Emre Akbaş's work include Advanced Neural Network Applications (6 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Image Retrieval and Classification Techniques (6 papers). Emre Akbaş is often cited by papers focused on Advanced Neural Network Applications (6 papers), Advanced Image and Video Retrieval Techniques (6 papers) and Image Retrieval and Classification Techniques (6 papers). Emre Akbaş collaborates with scholars based in Türkiye, United States and Australia. Emre Akbaş's co-authors include Miguel P. Eckstein, Fatoş T. Yarman Vural, Sinan Kalkan, Pınar Duygulu, Narendra Ahuja, Sheng Zhang, Stephen C. Mack, Fatoş T. Yarman-Vural, Mary A. Peterson and Kirsten Koehler and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Current Biology.

In The Last Decade

Emre Akbaş

25 papers receiving 260 citations

Peers

Emre Akbaş

CVPR

RNMI

Jun-Mo Kim South Korea

Swaminathan Gurumurthy United States

Hassan Farsi Iran

Zhaohui Che China

Nanne van Noord Netherlands

Yunzhi Zhuge China

Sanjay Ghosh India

Shi Chen China

Corneliu Florea Romania

Jun-Mo Kim South Korea

Emre Akbaş

180 ×1.0

CVPR

45 ×0.6

47 ×0.8

29 ×0.7

29 ×1.8

RNMI

Citations per year, relative to Emre Akbaş Emre Akbaş (= 1×) peers Jun-Mo Kim

Countries citing papers authored by Emre Akbaş

Since Specialization

Citations

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

Fields of papers citing papers by Emre Akbaş

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emre Akbaş

This figure shows the co-authorship network connecting the top 25 collaborators of Emre Akbaş. A scholar is included among the top collaborators of Emre Akbaş 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 Emre Akbaş. Emre Akbaş 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

Rekavandi, Aref Miri, et al.. (2025). Transformers in Small Object Detection: A Benchmark and Survey of State-of-the-Art. ACM Computing Surveys. 58(3). 1–33. 4 indexed citations

Güner, Güneş, et al.. (2025). Colorectal cancer tumor grade segmentation: A new dataset and baseline results. Heliyon. 11(4). e42467–e42467.

Kalkan, Sinan, et al.. (2024). RankED: Addressing Imbalance and Uncertainty in Edge Detection Using Ranking-based Losses. OpenMETU (Middle East Technical University). 3239–3249. 6 indexed citations

Akbaş, Emre, et al.. (2024). A multi-level multi-label text classification dataset of 19th century Ottoman and Russian literary and critical texts. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 6585–6596.

Hashmani, R. K., Emre Akbaş, & B. Demirköz. (2024). A comparison of deep learning models for proton background rejection with the AMS electromagnetic calorimeter. Machine Learning Science and Technology. 5(4). 45008–45008.

Akbaş, Emre, et al.. (2024). Dense depth alignment for human pose and shape estimation. Signal Image and Video Processing. 18(12). 8577–8584. 1 indexed citations

Pekcan, Onur, et al.. (2024). AIDCON: An Aerial Image Dataset and Benchmark for Construction Machinery. Remote Sensing. 16(17). 3295–3295. 1 indexed citations

Akbaş, Emre, et al.. (2024). MoCap-to-Visual Domain Adaptation for Efficient Human Mesh Estimation from 2D Keypoints. 1622–1632.

Kalkan, Sinan, et al.. (2023). Correlation Loss: Enforcing Correlation between Classification and Localization. Proceedings of the AAAI Conference on Artificial Intelligence. 37(1). 1087–1095. 3 indexed citations

10.

Akbaş, Emre, et al.. (2023). Improving Sketch Colorization Using Adversarial Segmentation Consistency. SSRN Electronic Journal.

11.

Akbaş, Emre, et al.. (2022). Just noticeable difference for machine perception and generation of regularized adversarial images with minimal perturbation. Signal Image and Video Processing. 16(6). 1595–1606. 1 indexed citations

12.

Akbaş, Emre, et al.. (2021). Automated learning rate search using batch-level cross-validation. SHILAP Revista de lepidopterología. 4(3). 312–325. 2 indexed citations

13.

Akbaş, Emre, et al.. (2020). GANILLA: Generative adversarial networks for image to illustration translation. Image and Vision Computing. 95. 103886–103886. 38 indexed citations

14.

Akbaş, Emre & Miguel P. Eckstein. (2017). Object detection through search with a foveated visual system. PLoS Computational Biology. 13(10). e1005743–e1005743. 43 indexed citations

15.

Eckstein, Miguel P., et al.. (2017). Humans, but Not Deep Neural Networks, Often Miss Giant Targets in Scenes. Current Biology. 27(18). 2827–2832.e3. 48 indexed citations

16.

Eckstein, Miguel P., et al.. (2015). Optimal and human eye movements to clustered low value cues to increase decision rewards during search. Vision Research. 113. 137–154. 21 indexed citations

17.

Akbaş, Emre & Narendra Ahuja. (2014). Low-Level Hierarchical Multiscale Segmentation Statistics of Natural Images. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(9). 1900–1906. 6 indexed citations

18.

Koehler, Kirsten, Emre Akbaş, Mary A. Peterson, & Miguel P. Eckstein. (2012). Human versus Bayesian Optimal Learning of Eye Movement Strategies During Visual Search. Journal of Vision. 12(9). 1142–1142. 3 indexed citations

19.

Akbaş, Emre & Narendra Ahuja. (2010). Low-Level Image Segmentation Based Scene Classification. OpenMETU (Middle East Technical University). 35. 3623–3626. 6 indexed citations

20.

Akbaş, Emre, et al.. (2006). A Hierarchical Classification System Based on Adaptive Resonance Theory. OpenMETU (Middle East Technical University). 27. 2913–2916. 7 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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