Nathan D. Kalka

1.9k total citations · 1 hit paper
25 papers, 1.1k citations indexed

About

Nathan D. Kalka is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Media Technology. According to data from OpenAlex, Nathan D. Kalka has authored 25 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 16 papers in Signal Processing and 4 papers in Media Technology. Recurrent topics in Nathan D. Kalka's work include Biometric Identification and Security (16 papers), Face recognition and analysis (12 papers) and Face and Expression Recognition (9 papers). Nathan D. Kalka is often cited by papers focused on Biometric Identification and Security (16 papers), Face recognition and analysis (12 papers) and Face and Expression Recognition (9 papers). Nathan D. Kalka collaborates with scholars based in United States. Nathan D. Kalka's co-authors include Bojan Čukić, Anil K. Jain, James A. Duncan, Tim Miller, Patrick Grother, Natalia A. Schmid, Jinyu Zuo, Charles Otto, Janet Anderson and Arun Ross and has published in prestigious journals such as Computer Vision and Image Understanding, Forensic Science International and IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans.

In The Last Decade

Nathan D. Kalka

25 papers receiving 1.0k 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.

IARPA Janus Benchmark - C: Face Dataset and Protocol

2018 364 citations James A. Duncan, Nathan D. Kalka et al. profile →

Peers

Nathan D. Kalka

CVPR

SP

AI

IS

MT

Elham Tabassi United States

Samarth Bharadwaj India

Tejas I. Dhamecha India

Cunjian Chen United States

Yihua Shi China

Byung Jun Kang South Korea

Xunqiang Tao China

Robert W. Ives United States

Jukka Komulainen Finland

Elham Tabassi United States

Nathan D. Kalka

464 ×0.5

CVPR

446 ×0.7

SP

84 ×0.8

AI

109 ×1.3

IS

23 ×0.3

MT

Citations per year, relative to Nathan D. Kalka Nathan D. Kalka (= 1×) peers Elham Tabassi

Countries citing papers authored by Nathan D. Kalka

Since Specialization

Citations

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

Fields of papers citing papers by Nathan D. Kalka

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nathan D. Kalka

This figure shows the co-authorship network connecting the top 25 collaborators of Nathan D. Kalka. A scholar is included among the top collaborators of Nathan D. Kalka 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 D. Kalka. Nathan D. Kalka 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

1.

Kalka, Nathan D., James A. Duncan, Jeremy Dawson, & Charles Otto. (2019). IARPA Janus Benchmark Multi-Domain Face. 1–9. 4 indexed citations

2.

Anderson, Janet, et al.. (2019). Understanding Confounding Factors in Face Detection and Recognition. 1–8. 2 indexed citations

3.

Kalka, Nathan D., et al.. (2019). Video Face Recognition: Component-wise Feature Aggregation Network (C-FAN). 1–8. 31 indexed citations

4.

Kalka, Nathan D., et al.. (2018). IJB–S: IARPA Janus Surveillance Video Benchmark. 1–9. 32 indexed citations

5.

Whitelam, Cameron, Austin Blanton, Tim Miller, et al.. (2017). IARPA Janus Benchmark-B Face Dataset. 592–600. 256 indexed citations

6.

Blanton, Austin, Kristen Allen, Tim Miller, Nathan D. Kalka, & Anil K. Jain. (2016). A Comparison of Human and Automated Face Verification Accuracy on Unconstrained Image Sets. 229–236. 13 indexed citations

7.

Allen, Kristen, et al.. (2016). Grouper: Optimizing Crowdsourced Face Annotations. 163–170. 3 indexed citations

8.

Kalka, Nathan D. & R. Austin Hicklin. (2014). On relative distortion in fingerprint comparison. Forensic Science International. 244. 78–84. 9 indexed citations

9.

Kalka, Nathan D., Thirimachos Bourlai, Bojan Čukić, & Lawrence A. Hornak. (2012). Cross-spectral face recognition in heterogeneous environments: A case study on matching visible to short-wave infrared imagery. 9 indexed citations

10.

Whitelam, Cameron, et al.. (2012). SWIR imaging for facial image capture through tinted materials. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 8353. 83530S–83530S. 2 indexed citations

11.

Kalka, Nathan D., Thirimachos Bourlai, Bojan Čukić, & Lawrence A. Hornak. (2011). Cross-spectral face recognition in heterogeneous environments: A case study on matching visible to short-wave infrared imagery. 1–8. 32 indexed citations

12.

Bourlai, Thirimachos, Nathan D. Kalka, Arun Ross, Bojan Čukić, & Lawrence A. Hornak. (2010). Cross-Spectral Face Verification in the Short Wave Infrared (SWIR) Band. 1343–1347. 51 indexed citations

13.

Kalka, Nathan D., Jinyu Zuo, Natalia A. Schmid, & Bojan Čukić. (2010). Estimating and Fusing Quality Factors for Iris Biometric Images. IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans. 40(3). 509–524. 73 indexed citations

14.

Kalka, Nathan D., et al.. (2009). Identifying sensors from fingerprint images. 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 78–84. 22 indexed citations

15.

Kalka, Nathan D., et al.. (2009). An automated method for predicting iris segmentation failures. 1–8. 3 indexed citations

16.

Kalka, Nathan D., et al.. (2009). Decision dependability and its application to identity management. 1–4. 1 indexed citations

17.

Yao, Yi, Besma Abidi, Nathan D. Kalka, Natalia A. Schmid, & Mongi A. Abidi. (2007). Improving long range and high magnification face recognition: Database acquisition, evaluation, and enhancement. Computer Vision and Image Understanding. 111(2). 111–125. 39 indexed citations

18.

Kalka, Nathan D., et al.. (2007). Protecting Iris Images through Asymmetric Digital Watermarking. 192–197. 25 indexed citations

19.

Kalka, Nathan D., Jinyu Zuo, Natalia A. Schmid, & Bojan Čukić. (2006). Image quality assessment for iris biometric. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6202. 62020D–62020D. 100 indexed citations

20.

Yao, Yi, Besma Abidi, Nathan D. Kalka, Natalia A. Schmid, & Mongi A. Abidi. (2006). High Magnification and Long Distance Face Recognition: Database Acquisition, Evaluation, and Enhancement. 1–6. 6 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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