Jan Feyereisl

481 total citations
12 papers, 183 citations indexed

About

Jan Feyereisl is a scholar working on Biomedical Engineering, Computer Vision and Pattern Recognition and Immunology. According to data from OpenAlex, Jan Feyereisl has authored 12 papers receiving a total of 183 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Biomedical Engineering, 4 papers in Computer Vision and Pattern Recognition and 4 papers in Immunology. Recurrent topics in Jan Feyereisl's work include Artificial Immune Systems Applications (6 papers), T-cell and B-cell Immunology (4 papers) and Gene expression and cancer classification (2 papers). Jan Feyereisl is often cited by papers focused on Artificial Immune Systems Applications (6 papers), T-cell and B-cell Immunology (4 papers) and Gene expression and cancer classification (2 papers). Jan Feyereisl collaborates with scholars based in United Kingdom, Australia and South Korea. Jan Feyereisl's co-authors include Uwe Aickelin, Bohyung Han, Julie Greensmith, Yihui Liu, Lindy G. Durrant, Jeany Son, Larry S. Davis, Jonghyun Choi, Suha Kwak and Seunghoon Hong and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Pattern Analysis and Machine Intelligence and Information Sciences.

In The Last Decade

Jan Feyereisl

12 papers receiving 176 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jan Feyereisl United Kingdom	6	77	73	41	23	20	12	183
Leiguang Gong United States	8	112 1.5×	76 1.0×	13 0.3×	11 0.5×	26 1.3×	29	191
Gurram Sunitha India	6	74 1.0×	56 0.8×	9 0.2×	12 0.5×	8 0.4×	26	196
Luiz Cláudio Navarro Brazil	7	62 0.8×	16 0.2×	10 0.2×	37 1.6×	33 1.6×	16	177
Greg Ross United Kingdom	6	109 1.4×	45 0.6×	34 0.8×	55 2.4×	12 0.6×	8	189
Reza Moradi Rad Canada	12	228 3.0×	109 1.5×	13 0.3×	24 1.0×	23 1.1×	23	388
Arpan Basu India	8	60 0.8×	175 2.4×	13 0.3×	6 0.3×	7 0.3×	13	283
Filipe Soares Portugal	9	83 1.1×	55 0.8×	10 0.2×	5 0.2×	15 0.8×	26	269
T. Kar India	7	93 1.2×	81 1.1×	17 0.4×	34 1.5×	5 0.3×	28	225

Countries citing papers authored by Jan Feyereisl

Since Specialization

Citations

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

Fields of papers citing papers by Jan Feyereisl

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Feyereisl

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

All Works

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12 of 12 papers shown

Davidson, Joseph K., et al.. (2020). ToyArchitecture: Unsupervised learning of interpretable models of the environment. PLoS ONE. 15(5). e0230432–e0230432. 4 indexed citations

Hong, Seunghoon, Jonghyun Choi, Jan Feyereisl, Bohyung Han, & Larry S. Davis. (2015). Joint Image Clustering and Labeling by Matrix Factorization. IEEE Transactions on Pattern Analysis and Machine Intelligence. 38(7). 1411–1424. 31 indexed citations

Feyereisl, Jan, Suha Kwak, Jeany Son, & Bohyung Han. (2014). Object Localization based on Structural SVM using Privileged Information. Open Access System for Information Sharing (Pohang University of Science and Technology). 27. 208–216. 24 indexed citations

Liu, Yihui, Uwe Aickelin, Jan Feyereisl, & Lindy G. Durrant. (2013). Wavelet Feature Extraction and Genetic Algorithm for Biomarker Detection in Colorectal Cancer Data. SSRN Electronic Journal. 1 indexed citations

Liu, Yihui, Uwe Aickelin, Jan Feyereisl, & Lindy G. Durrant. (2012). Wavelet feature extraction and genetic algorithm for biomarker detection in colorectal cancer data. Knowledge-Based Systems. 37. 502–514. 29 indexed citations

Feyereisl, Jan & Uwe Aickelin. (2011). Privileged information for data clustering. Information Sciences. 194. 4–23. 48 indexed citations

Feyereisl, Jan & Uwe Aickelin. (2009). SELF-ORGANISING MAPS IN COMPUTER SECURITY. SSRN Electronic Journal. 2 indexed citations

Aickelin, Uwe, Julie Greensmith, & Jan Feyereisl. (2008). The DCA: Some Comparison a Comparative Study between Two Biologically-Inspired Algorithms. SSRN Electronic Journal. 5 indexed citations

Somayaji, Anil, Michael E. Locasto, & Jan Feyereisl. (2008). The future of biologically-inspired security. 49–54. 13 indexed citations

10.

Greensmith, Julie, Jan Feyereisl, & Uwe Aickelin. (2008). The DCA: SOMe comparison. Evolutionary Intelligence. 1(2). 85–112. 24 indexed citations

11.

Feyereisl, Jan & Uwe Aickelin. (2006). Artificial Immune Tissue using Self-Organizing Networks. Nottingham ePrints (University of Nottingham). 1. 1 indexed citations

12.

Feyereisl, Jan & Uwe Aickelin. (2006). Artificial Immune Tissue Using Self-Organizing Networks. SSRN Electronic Journal. 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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