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Software . 2023
License: CC BY
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ZENODO
Software . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test: Code

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 04 Jul 2023 English Publisher:Zenodo
Authors: Behnam Khojasteh; Friedrich Solowjow; Sebastian Trimpe; Katherine J. Kuchenbecker;

doi: 10.5281/zenodo.8077638 , 10.5281/zenodo.8077639

Multimodal Multi-User Surface Recognition with the Kernel Two-Sample Test: Code

Abstract

This open-source code generates the results of the publication "Multimodal Multi-user Surface Recognition with the Kernel Two-Sample Test" by Behnam Khojasteh, Friedrich Solowjow, Sebastian Trimpe, and Katherine J. Kuchenbecker in the IEEE journal "Transactions on Automation Science and Engineering" (T-ASE). Complete changelog is provided in following GitHub repository: https://github.com/bkhojasteh/surfaceRecognition_LMT108

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Keywords

kernel methods, two-sample test, time series, surface recognition

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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