Gencer Sumbül

1.0k total citations · 1 hit paper
27 papers, 640 citations indexed

About

Gencer Sumbül is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence. According to data from OpenAlex, Gencer Sumbül has authored 27 papers receiving a total of 640 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 18 papers in Media Technology and 7 papers in Artificial Intelligence. Recurrent topics in Gencer Sumbül's work include Remote-Sensing Image Classification (18 papers), Advanced Image and Video Retrieval Techniques (17 papers) and Image Retrieval and Classification Techniques (14 papers). Gencer Sumbül is often cited by papers focused on Remote-Sensing Image Classification (18 papers), Advanced Image and Video Retrieval Techniques (17 papers) and Image Retrieval and Classification Techniques (14 papers). Gencer Sumbül collaborates with scholars based in Germany, Switzerland and Italy. Gencer Sumbül's co-authors include Begüm Demir, Volker Markl, Marcela Charfuelàn, Mahdyar Ravanbakhsh, Lorenzo Bruzzone, Markus P. Müller, Mário Caetano, Pedro Benevides, Hugo Costa and Genc Hoxha and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Gencer Sumbül

23 papers receiving 609 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Bigearthnet: A Large-Scale Benchmark Archive for Remote Sensing Image Understanding

2019 338 citations Gencer Sumbül, Marcela Charfuelàn et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Gencer Sumbül Germany	10	348	310	194	101	80	27	640
Laila Bashmal Saudi Arabia	10	332 1.0×	345 1.1×	181 0.9×	93 0.9×	147 1.8×	17	701
Weixun Zhou China	5	485 1.4×	453 1.5×	123 0.6×	78 0.8×	100 1.3×	6	665
Xianping Ma China	10	315 0.9×	264 0.9×	88 0.5×	39 0.4×	98 1.2×	28	551
Giovanni Marchisio United States	12	377 1.1×	284 0.9×	80 0.4×	122 1.2×	118 1.5×	33	619
Chenyang Liu China	13	342 1.0×	389 1.3×	143 0.7×	68 0.7×	155 1.9×	23	836
Xizhe Xue China	7	193 0.6×	169 0.5×	88 0.5×	82 0.8×	84 1.1×	13	461
Guangyi Yang China	12	430 1.2×	290 0.9×	64 0.3×	135 1.3×	181 2.3×	30	704
Wanxuan Lu China	9	235 0.7×	226 0.7×	108 0.6×	34 0.3×	63 0.8×	23	499
Yuxi Sun China	10	289 0.8×	234 0.8×	91 0.5×	42 0.4×	168 2.1×	25	606
Yin Zhuang China	15	417 1.2×	412 1.3×	92 0.5×	66 0.7×	94 1.2×	64	754

Countries citing papers authored by Gencer Sumbül

Since Specialization

Citations

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

Fields of papers citing papers by Gencer Sumbül

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gencer Sumbül

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

Sumbül, Gencer, et al.. (2025). MaskSDM with Shapley values to improve flexibility, robustness and explainability in species distribution modelling. Methods in Ecology and Evolution. 17(1). 188–206.

Sumbül, Gencer, et al.. (2025). reBen: Refined BigEarthNet Dataset for Remote Sensing Image Analysis. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 1264–1268. 1 indexed citations

Sumbül, Gencer, et al.. (2024). Federated Learning Across Decentralized and Unshared Archives for Remote Sensing Image Classification: A review. IEEE Geoscience and Remote Sensing Magazine. 12(3). 64–80. 5 indexed citations

Sumbül, Gencer, et al.. (2024). Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–14. 2 indexed citations

Hoxha, Genc, et al.. (2024). Annotation Cost-Efficient Active Learning for Deep Metric Learning-Driven Remote Sensing Image Retrieval. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–11.

Hoxha, Genc, et al.. (2023). Annotation Cost Efficient Active Learning for Content Based Image Retrieval. 4994–4997. 2 indexed citations

Sumbül, Gencer & Begüm Demir. (2023). Label Noise Robust Image Representation Learning Based on Supervised Variational Autoencoders in Remote Sensing. 646–649.

Sumbül, Gencer, et al.. (2022). Deep Metric Learning-Based Semi-Supervised Regression with Alternate Learning. 2022 IEEE International Conference on Image Processing (ICIP). 2411–2415. 4 indexed citations

Sumbül, Gencer, Mahdyar Ravanbakhsh, & Begüm Demir. (2022). A Relevant, Hard and Diverse Triplet Sampling Method for Multi-Label Remote Sensing Image Retrieval. 5–8. 2 indexed citations

10.

Sumbül, Gencer, Markus P. Müller, & Begüm Demir. (2022). A Novel Self-Supervised Cross-Modal Image Retrieval Method in Remote Sensing. 2022 IEEE International Conference on Image Processing (ICIP). 2426–2430. 6 indexed citations

11.

Sumbül, Gencer, et al.. (2022). A Novel Framework to Jointly Compress and Index Remote Sensing Images for Efficient Content-Based Retrieval. IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. 13. 251–254. 1 indexed citations

12.

Sumbül, Gencer, Hugo Costa, Pedro Benevides, et al.. (2021). BigEarthNet-MM: A Large-Scale, Multimodal, Multilabel Benchmark Archive for Remote Sensing Image Classification and Retrieval [Software and Data Sets]. Revista de Estudos Anglo-Portugueses/Journal of Anglo-Portuguese Studies. 4 indexed citations

13.

Sumbül, Gencer, Mahdyar Ravanbakhsh, & Begüm Demir. (2021). Informative and Representative Triplet Selection for Multilabel Remote Sensing Image Retrieval. arXiv (Cornell University). 27 indexed citations

14.

Sumbül, Gencer, et al.. (2020). Remote-Sensing Image Scene Classification With Deep Neural Networks in JPEG 2000 Compressed Domain. IEEE Transactions on Geoscience and Remote Sensing. 59(4). 3458–3472. 15 indexed citations

15.

Sumbül, Gencer, et al.. (2020). A Comparative Study of Deep Learning Loss Functions for Multi-Label Remote Sensing Image Classification. arXiv (Cornell University). 36 indexed citations

16.

Sumbül, Gencer, et al.. (2020). SD-RSIC: Summarization-Driven Deep Remote Sensing Image Captioning. IEEE Transactions on Geoscience and Remote Sensing. 59(8). 6922–6934. 72 indexed citations

17.

Sumbül, Gencer, Jian Kang, Hugo Costa, et al.. (2020). BigEarthNet Deep Learning Models with A New Class-Nomenclature for Remote Sensing Image Understanding.. 1 indexed citations

18.

Sumbül, Gencer & Begüm Demir. (2020). A Deep Multi-Attention Driven Approach for Multi-Label Remote Sensing Image Classification. IEEE Access. 8. 95934–95946. 44 indexed citations

19.

Sumbül, Gencer, Marcela Charfuelàn, Begüm Demir, & Volker Markl. (2019). Bigearthnet: A Large-Scale Benchmark Archive for Remote Sensing Image Understanding. arXiv (Cornell University). 5901–5904. 338 indexed citations breakdown →

20.

Sumbül, Gencer & Begüm Demir. (2019). A CNN-RNN Framework with a Novel Patch-Based Multi-Attention Mechanism for Multi-Label Image Classification in Remote Sensing.. arXiv (Cornell University). 2 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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