Nathan Drenkow

466 total citations
13 papers, 232 citations indexed

About

Nathan Drenkow is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nathan Drenkow has authored 13 papers receiving a total of 232 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 3 papers in Molecular Biology and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nathan Drenkow's work include Adversarial Robustness in Machine Learning (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Image Processing Techniques and Applications (2 papers). Nathan Drenkow is often cited by papers focused on Adversarial Robustness in Machine Learning (2 papers), Advanced Image and Video Retrieval Techniques (2 papers) and Image Processing Techniques and Applications (2 papers). Nathan Drenkow collaborates with scholars based in United States and Italy. Nathan Drenkow's co-authors include Mathias Unberath, Andy S. Ding, Xingtong Liu, Russell H. Taylor, Francis X. Creighton, Zhaoshuo Li, Ilya Shpitser, Philippe Burlina, Brock A. Wester and William Gray-Roncal and has published in prestigious journals such as Scientific Reports, Frontiers in Psychology and GigaScience.

In The Last Decade

Nathan Drenkow

13 papers receiving 226 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Nathan Drenkow United States	5	170	45	41	33	17	13	232
Runjian Chen China	6	124 0.7×	52 1.2×	27 0.7×	47 1.4×	11 0.6×	11	224
Changsheng Lu China	7	188 1.1×	35 0.8×	60 1.5×	25 0.8×	21 1.2×	16	243
Mengyang Pu China	7	198 1.2×	24 0.5×	51 1.2×	71 2.2×	8 0.5×	13	287
Oliver Wasenmüller Germany	9	189 1.1×	122 2.7×	19 0.5×	26 0.8×	11 0.6×	29	280
Chaitanya Desai United States	7	393 2.3×	40 0.9×	33 0.8×	129 3.9×	9 0.5×	10	446
Seungeui Lee South Korea	4	178 1.0×	44 1.0×	17 0.4×	131 4.0×	15 0.9×	6	250
Zigang Geng China	5	291 1.7×	29 0.6×	23 0.6×	109 3.3×	60 3.5×	5	353
Stavros Tsogkas Canada	8	191 1.1×	30 0.7×	13 0.3×	55 1.7×	22 1.3×	10	250
Kun Yan China	10	164 1.0×	97 2.2×	9 0.2×	36 1.1×	10 0.6×	25	240

Countries citing papers authored by Nathan Drenkow

Since Specialization

Citations

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

Fields of papers citing papers by Nathan Drenkow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nathan Drenkow

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

All Works

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13 of 13 papers shown

Drenkow, Nathan, et al.. (2024). From generalization to precision: exploring SAM for tool segmentation in surgical environments. arXiv (Cornell University). 2–2. 3 indexed citations

Drenkow, Nathan & Mathias Unberath. (2024). RobustCLEVR: A Benchmark and Framework for Evaluating Robustness in Object-centric Learning. 4506–4515. 1 indexed citations

Drenkow, Nathan, et al.. (2023). Semi-supervised domain transfer for robust maritime satellite image classification. 37–37. 1 indexed citations

Johnson, Erik C., et al.. (2022). A framework for rigorous evaluation of human performance in human and machine learning comparison studies. Scientific Reports. 12(1). 13 indexed citations

Drenkow, Nathan, et al.. (2022). Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 2815–2825. 5 indexed citations

Gray-Roncal, William, et al.. (2021). Benchmarking Human Performance for Visual Search of Aerial Images. Frontiers in Psychology. 12. 733021–733021. 2 indexed citations

Li, Zhaoshuo, Xingtong Liu, Nathan Drenkow, et al.. (2021). Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 6177–6186. 175 indexed citations

Drenkow, Nathan, et al.. (2021). A Systematic Review of Robustness in Deep Learning for Computer Vision: Mind the gap?. arXiv (Cornell University). 18 indexed citations

Johnson, Erik C., Luis M. Rodríguez, Corban G. Rivera, et al.. (2020). Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets. GigaScience. 9(12). 3 indexed citations

10.

Gardner, Ryan W., et al.. (2019). The First International Competition in Machine Reconnaissance Blind Chess. 121–130. 2 indexed citations

11.

Drenkow, Nathan, et al.. (2018). CIRCUIT summer program: A computational neuroscience outreach experience for high-achieving undergraduates via sponsored research. 31. 45–52. 3 indexed citations

12.

Zhou, Jie, Zhi Zhou, Alessandro Bria, et al.. (2016). Bioimage Informatics for Big Data. Advances in anatomy, embryology and cell biology. 219. 263–272. 5 indexed citations

13.

Rodríguez, Pedro, et al.. (2014). Selection of universal features for image classification. 45. 355–362. 1 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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