Ian Fasel

57 total papers · 4.4k total citations
42 papers, 3.0k citations indexed

About

Ian Fasel is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Ian Fasel has authored 42 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Vision and Pattern Recognition, 17 papers in Artificial Intelligence and 12 papers in Experimental and Cognitive Psychology. Recurrent topics in Ian Fasel's work include Face and Expression Recognition (13 papers), Emotion and Mood Recognition (11 papers) and Face recognition and analysis (10 papers). Ian Fasel is often cited by papers focused on Face and Expression Recognition (13 papers), Emotion and Mood Recognition (11 papers) and Face recognition and analysis (10 papers). Ian Fasel collaborates with scholars based in United States, Japan and Italy. Ian Fasel's co-authors include Javier R. Movellan, Marian Stewart Bartlett, Gwen Littlewort, Mark G. Frank, Claudia Lainscsek, Jacob Whitehill, Joshua M. Susskind, Tingfan Wu, Bret Fortenberry and Jeffrey Berry and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, The Journal of the Acoustical Society of America and Pattern Recognition Letters.

In The Last Decade

Ian Fasel

42 papers receiving 2.8k citations

Hit Papers

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Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Ian Fasel 1.9k 1.7k 504 499 454 42 3.0k
Gwen Littlewort 2.1k 1.1× 2.2k 1.3× 876 1.7× 555 1.1× 463 1.0× 38 3.6k
Peter W. McOwan 2.3k 1.2× 1.8k 1.1× 665 1.3× 596 1.2× 527 1.2× 92 3.9k
Zhihong Zeng 1.3k 0.7× 1.8k 1.1× 459 0.9× 538 1.1× 513 1.1× 79 3.0k
Mohammad H. Mahoor 2.5k 1.3× 2.2k 1.3× 917 1.8× 506 1.0× 637 1.4× 134 4.6k
Léon Rothkrantz 2.0k 1.0× 1.8k 1.1× 524 1.0× 445 0.9× 825 1.8× 160 4.2k
Miyuki Kamachi 1.5k 0.8× 1.3k 0.8× 685 1.4× 330 0.7× 354 0.8× 32 2.6k
Patrick Lucey 3.3k 1.7× 2.6k 1.6× 573 1.1× 311 0.6× 619 1.4× 71 4.7k
Michael J. Lyons 2.8k 1.4× 1.5k 0.9× 531 1.1× 251 0.5× 561 1.2× 61 3.7k
Jiro Gyoba 1.5k 0.8× 1.5k 0.9× 1.1k 2.3× 496 1.0× 342 0.8× 122 3.1k
Zara Ambadar 2.9k 1.5× 3.1k 1.8× 1.1k 2.3× 681 1.4× 395 0.9× 24 4.6k

Countries citing papers authored by Ian Fasel

Since Specialization
Citations

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

Fields of papers citing papers by Ian Fasel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ian Fasel

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

All Works

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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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