Minna Pakanen

60 total papers · 508 total citations
48 papers, 340 citations indexed

About

Minna Pakanen is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Minna Pakanen has authored 48 papers receiving a total of 340 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Human-Computer Interaction, 13 papers in Computer Vision and Pattern Recognition and 8 papers in Cognitive Neuroscience. Recurrent topics in Minna Pakanen's work include Virtual Reality Applications and Impacts (21 papers), Innovative Human-Technology Interaction (20 papers) and Interactive and Immersive Displays (19 papers). Minna Pakanen is often cited by papers focused on Virtual Reality Applications and Impacts (21 papers), Innovative Human-Technology Interaction (20 papers) and Interactive and Immersive Displays (19 papers). Minna Pakanen collaborates with scholars based in Finland, Denmark and Netherlands. Minna Pakanen's co-authors include Timo Ojala, Leena Arhippainen, Jonna Häkkilä, Timo Koskela, Ashley Colley, Niels van Berkel, Hannu Kukka, Matti Pouke, Berry Eggen and Johan Kildal and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACM Transactions on Computer-Human Interaction and Multimedia Tools and Applications.

In The Last Decade

Minna Pakanen

46 papers receiving 323 citations

Author Peers

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

Author						Papers	Cites
Minna Pakanen	246	92	54	40	39	48	340
Leena Arhippainen	174 0.7×	79 0.9×	52 1.0×	21 0.5×	38 1.0×	39	314
Atsushi Hiyama	184 0.7×	84 0.9×	113 2.1×	38 0.9×	20 0.5×	53	339
Albert N. Badre	152 0.6×	88 1.0×	50 0.9×	60 1.5×	29 0.7×	25	369
Donald Degraen	225 0.9×	97 1.1×	97 1.8×	37 0.9×	36 0.9×	36	338
Matjaž Kljun	190 0.8×	167 1.8×	51 0.9×	29 0.7×	36 0.9×	41	345
Adrian Bullock	190 0.8×	90 1.0×	40 0.7×	55 1.4×	61 1.6×	24	339
Alexander Wiethoff	319 1.3×	138 1.5×	109 2.0×	36 0.9×	35 0.9×	44	391
Nina Valkanova	316 1.3×	104 1.1×	95 1.8×	16 0.4×	56 1.4×	16	400
Alberto Cannavò	210 0.9×	163 1.8×	39 0.7×	55 1.4×	19 0.5×	44	399
Pablo Figueroa	196 0.8×	117 1.3×	49 0.9×	28 0.7×	17 0.4×	64	316

Countries citing papers authored by Minna Pakanen

Since Specialization

Citations

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

Fields of papers citing papers by Minna Pakanen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minna Pakanen

This figure shows the co-authorship network connecting the top 25 collaborators of Minna Pakanen. A scholar is included among the top collaborators of Minna Pakanen 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 Minna Pakanen. Minna Pakanen 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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