Arjuna Flenner

904 total citations
20 papers, 448 citations indexed

About

Arjuna Flenner is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Arjuna Flenner has authored 20 papers receiving a total of 448 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 4 papers in Computational Theory and Mathematics. Recurrent topics in Arjuna Flenner's work include Medical Image Segmentation Techniques (4 papers), Image Retrieval and Classification Techniques (4 papers) and Topological and Geometric Data Analysis (4 papers). Arjuna Flenner is often cited by papers focused on Medical Image Segmentation Techniques (4 papers), Image Retrieval and Classification Techniques (4 papers) and Topological and Geometric Data Analysis (4 papers). Arjuna Flenner collaborates with scholars based in United States, Sweden and Italy. Arjuna Flenner's co-authors include Andrea L. Bertozzi, Lakshmanan Nataraj, Tajuddin Manhar Mohammed, Amit K. Roy–Chowdhury, B.S. Manjunath, Shivkumar Chandrasekaran, Jawadul H. Bappy, Allon G. Percus, Cristina García–Cardona and Ekaterina Merkurjev and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of the Association for Information Systems and SIAM Review.

In The Last Decade

Arjuna Flenner

19 papers receiving 419 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arjuna Flenner United States 8 254 121 74 54 52 20 448
Yves van Gennip United Kingdom 10 117 0.5× 56 0.5× 79 1.1× 65 1.2× 40 0.8× 26 320
Sébastien Bougleux France 9 392 1.5× 148 1.2× 82 1.1× 126 2.3× 101 1.9× 19 592
Basarab Mateï France 10 180 0.7× 60 0.5× 26 0.4× 119 2.2× 48 0.9× 44 362
Yifan Chen United States 11 51 0.2× 140 1.2× 32 0.4× 44 0.8× 23 0.4× 47 383
Mauro Piccioni Italy 13 203 0.8× 180 1.5× 68 0.9× 59 1.1× 16 0.3× 41 583
Xueju Shen China 14 629 2.5× 211 1.7× 42 0.6× 11 0.2× 115 2.2× 67 759
Lê Minh Hiếu Vietnam 11 317 1.2× 81 0.7× 16 0.2× 55 1.0× 151 2.9× 34 577
Junzheng Jiang China 10 103 0.4× 137 1.1× 21 0.3× 41 0.8× 26 0.5× 47 336
Gang-Joon Yoon South Korea 11 149 0.6× 45 0.4× 54 0.7× 95 1.8× 26 0.5× 54 417
Verónica Fernández Spain 12 195 0.8× 282 2.3× 58 0.8× 15 0.3× 6 0.1× 37 770

Countries citing papers authored by Arjuna Flenner

Since Specialization
Citations

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

Fields of papers citing papers by Arjuna Flenner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arjuna Flenner

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

All Works

20 of 20 papers shown
1.
Flenner, Arjuna, et al.. (2024). Extracting explanations, justification, and uncertainty from black-box deep neural networks. 18. 8–8. 1 indexed citations
2.
Flenner, Arjuna, et al.. (2019). Deep Learning Methods for Event Verification and Image Repurposing Detection. Electronic Imaging. 31(5). 530–1. 4 indexed citations
3.
Flenner, Arjuna, et al.. (2019). Optimal Control for Improved UAV Communication. AIAA Scitech 2019 Forum. 3 indexed citations
4.
Flenner, Arjuna, et al.. (2019). Deep Models, Machine Learning, and Artificial Intelligence Applications in National and International Security — Part Two. AI Magazine. 40(2). 29–30. 1 indexed citations
5.
Flenner, Arjuna, et al.. (2019). Deep Models, Machine Learning, and Artificial Intelligence Applications in National and International Security. AI Magazine. 40(1). 35–36. 1 indexed citations
6.
Nataraj, Lakshmanan, Tajuddin Manhar Mohammed, B.S. Manjunath, et al.. (2019). Detecting GAN generated Fake Images using Co-occurrence Matrices. Electronic Imaging. 31(5). 532–1. 170 indexed citations
7.
Flenner, Arjuna, et al.. (2018). Resampling Forgery Detection Using Deep Learning and A-Contrario Analysis. Electronic Imaging. 30(7). 212–1. 13 indexed citations
8.
Flenner, Arjuna, Marlena R. Fraune, Laura M. Hiatt, et al.. (2018). Reports of the AAAI 2017 Fall Symposium Series. AI Magazine. 39(2). 81–86.
9.
Calatroni, Luca, Yves van Gennip, Carola‐Bibiane Schönlieb, Hannah M. Rowland, & Arjuna Flenner. (2017). Graph Clustering, Variational Image Segmentation Methods and Hough Transform Scale Detection for Object Measurement in Images. Apollo (University of Cambridge). 13 indexed citations
10.
Bertozzi, Andrea L. & Arjuna Flenner. (2016). Diffuse Interface Models on Graphs for Classification of High Dimensional Data. SIAM Review. 58(2). 293–328. 36 indexed citations
11.
Ma, Anna, Arjuna Flenner, Deanna Needell, & Allon G. Percus. (2014). Improving image clustering using sparse text and the wisdom of the crowds. 2014 48th Asilomar Conference on Signals, Systems and Computers. 1555–1557. 2 indexed citations
12.
Merkurjev, Ekaterina, Cristina García–Cardona, Andrea L. Bertozzi, Arjuna Flenner, & Allon G. Percus. (2014). Diffuse interface methods for multiclass segmentation of high-dimensional data. Applied Mathematics Letters. 33. 29–34. 30 indexed citations
13.
García–Cardona, Cristina, Ekaterina Merkurjev, Andrea L. Bertozzi, Arjuna Flenner, & Allon G. Percus. (2014). Multiclass Data Segmentation Using Diffuse Interface Methods on Graphs. IEEE Transactions on Pattern Analysis and Machine Intelligence. 36(8). 1600–1613. 71 indexed citations
14.
Olfman, Lorne, et al.. (2013). A Novel Business Intelligence Technique to Improve High Performance within an Organization Applying Insights from Hydrogeological Case. Journal of the Association for Information Systems. 19. 1259–61. 1 indexed citations
15.
Flenner, Arjuna, et al.. (2012). Lévy walks for autonomous search. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8389. 83890Z–83890Z. 4 indexed citations
16.
García–Cardona, Cristina, Arjuna Flenner, & Allon G. Percus. (2012). Multiclass Diffuse Interface Models for Semi-Supervised Learning on Graphs. arXiv (Cornell University). 78–86. 1 indexed citations
17.
Bertozzi, Andrea L. & Arjuna Flenner. (2012). Diffuse Interface Models on Graphs for Classification of High Dimensional Data. Multiscale Modeling and Simulation. 10(3). 1090–1118. 85 indexed citations
18.
Flenner, Arjuna & Gary A. Hewer. (2011). A Helmholtz Principle Approach to Parameter Free Change Detection and Coherent Motion Using Exchangeable Random Variables. SIAM Journal on Imaging Sciences. 4(1). 243–276. 9 indexed citations
19.
Flenner, Arjuna, Gary A. Hewer, & Charles Kenney. (2008). Two dimensional histogram analysis using the Helmholtz principle. Inverse Problems and Imaging. 2(4). 485–525. 2 indexed citations
20.
Flenner, Arjuna, et al.. (2006). Locating Peaks in Proteomic Mass Spectral Data Using the Morel-Helmholtz Principle. 31. 217–221. 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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