Citations per year, relative to Frank-Michael Schleif Frank-Michael Schleif (= 1×)
peers
Petr Somol
Countries citing papers authored by Frank-Michael Schleif
Since
Specialization
Citations
This map shows the geographic impact of Frank-Michael Schleif'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 Frank-Michael Schleif with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank-Michael Schleif more than expected).
Fields of papers citing papers by Frank-Michael Schleif
This network shows the impact of papers produced by Frank-Michael Schleif. 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 Frank-Michael Schleif. The network helps show where Frank-Michael Schleif may publish in the future.
Co-authorship network of co-authors of Frank-Michael Schleif
This figure shows the co-authorship network connecting the top 25 collaborators of Frank-Michael Schleif.
A scholar is included among the top collaborators of Frank-Michael Schleif 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 Frank-Michael Schleif. Frank-Michael Schleif is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Schleif, Frank-Michael, et al.. (2020). Random Projection in supervised non-stationary environments.. The European Symposium on Artificial Neural Networks. 405–410.1 indexed citations
Schleif, Frank-Michael, et al.. (2019). Towards a device-free passive presence detection system with Bluetooth Low Energy beacons.. The European Symposium on Artificial Neural Networks.5 indexed citations
Schleif, Frank-Michael, Andrej Gisbrecht, & Peter Tiňo. (2015). Probabilistic Classification Vector Machine at large scale.. University of Birmingham Research Portal (University of Birmingham).1 indexed citations
10.
Schleif, Frank-Michael. (2014). Proximity learning for non-standard big data.. The European Symposium on Artificial Neural Networks.4 indexed citations
11.
Villmann, Thomas, et al.. (2014). Advances in Self-Organizing Maps and Learning Vector Quantization: Proceedings of the 10th International Workshop, WSOM 2014, Mittweida, Germany. Springer eBooks.2 indexed citations
12.
Schleif, Frank-Michael, et al.. (2012). Fast approximated relational and kernel clustering. PUB – Publications at Bielefeld University (Bielefeld University).5 indexed citations
Schleif, Frank-Michael, et al.. (2009). Supervised data analysis and reliability estimation for spectral data. PUB – Publications at Bielefeld University (Bielefeld University).4 indexed citations
15.
Villmann, Thomas & Frank-Michael Schleif. (2009). Functional Vector Quantization by Neural Maps. PUB – Publications at Bielefeld University (Bielefeld University).4 indexed citations
16.
Schleif, Frank-Michael, et al.. (2007). Supervised Neural Gas for Functional Data and its Application to the Analysis of Clinical Proteom Spectra. PUB – Publications at Bielefeld University (Bielefeld University).2 indexed citations
17.
Villmann, Thomas, Marc Strickert, C. Bayan Bruss, Frank-Michael Schleif, & Udo Seiffert. (2007). Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS. The European Symposium on Artificial Neural Networks. 103–108.8 indexed citations
18.
Bruss, C. Bayan, et al.. (2006). Fuzzy Image Segmentation with Fuzzy Labelled Neural Gas. PUB – Publications at Bielefeld University (Bielefeld University). 563–568.6 indexed citations
19.
Schleif, Frank-Michael, Barbara Hammer, & Thomas Villmann. (2006). Margin based Active Learning for LVQ Networks. PUB – Publications at Bielefeld University (Bielefeld University). 539–544.1 indexed citations
20.
Villmann, T., Frank-Michael Schleif, & Barbara Hammer. (2003). Supervised Neural Gas and Relevance Learning in Learning Vector Quantization. PUB – Publications at Bielefeld University (Bielefeld University).9 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.