Michael D. Indovina

729 total citations
4 papers, 450 citations indexed

About

Michael D. Indovina is a scholar working on Signal Processing, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michael D. Indovina has authored 4 papers receiving a total of 450 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Signal Processing, 2 papers in Information Systems and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michael D. Indovina's work include Biometric Identification and Security (3 papers), User Authentication and Security Systems (2 papers) and Face recognition and analysis (2 papers). Michael D. Indovina is often cited by papers focused on Biometric Identification and Security (3 papers), User Authentication and Security Systems (2 papers) and Face recognition and analysis (2 papers). Michael D. Indovina collaborates with scholars based in United States. Michael D. Indovina's co-authors include Robert Snelick, Alan Mink, Anil K. Jain, Umut Uludağ, Michael D. Garris, Elham Tabassi, George Quinn, Patrick Grother and Craig I. Watson and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Michael D. Indovina

3 papers receiving 400 citations

Peers

Michael D. Indovina
Michael D. Indovina
Citations per year, relative to Michael D. Indovina Michael D. Indovina (= 1×) peers Pawel Drozdowski

Countries citing papers authored by Michael D. Indovina

Since Specialization
Citations

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

Fields of papers citing papers by Michael D. Indovina

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael D. Indovina

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

All Works

4 of 4 papers shown
1.
Indovina, Michael D., et al.. (2009). An Evaluation of Automated Latent Fingerprint Identification Technology (Phase II) | NIST. 5 indexed citations
2.
Grother, Patrick, et al.. (2007). Concepts of Operations (CONOPS) for the Evaluation of Latent Fingerprint Technologies (ELFT) | NIST.
3.
Snelick, Robert, Umut Uludağ, Alan Mink, Michael D. Indovina, & Anil K. Jain. (2005). Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems. IEEE Transactions on Pattern Analysis and Machine Intelligence. 27(3). 450–455. 356 indexed citations
4.
Indovina, Michael D., Robert Snelick, & Alan Mink. (2003). Multimodal Biometric Authentication Methods: A COTS Approach | NIST. 89 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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