‪Markus Eichhoff‬ - ‪Google Scholar‬

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	All	Since 2019
Citations	49	12
h-index	2	1
i10-index	1	1

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20122013201420152016201720182019202020212022202320242 10 6 8 7 2 2 1 3 4 3 1

Co-authors

Igor VatolkinAkademischer Rat, RWTH AachenVerified email at rwth-aachen.de
Mike PreussUniversiteit LeidenVerified email at liacs.leidenuniv.nl
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de

Markus Eichhoff

Markus Eichhoff

Unknown affiliation

Verified email at tu-dortmund.de

Classification Regression Clustering Deep Learning Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Multi-objective evolutionary feature selection for instrument recognition in polyphonic audio mixtures I Vatolkin, M Preuß, G Rudolph, M Eichhoff, C Weihs Soft Computing 16, 2027-2047, 2012	37	2012
Musical Instrument Recognition by High-Level Features M Eichhoff, C Weihs Challenges at the Interface of Data Analysis, Computer Science, and …, 2012	7	2012
Selecting Groups of Audio Features by Statistical Tests and the Group Lasso. B Bischl, M Eichhoff, C Weihs Sprachkommunikation, 1-4, 2010	2	2010
Recognition of musical instruments in intervals and chords M Eichhoff, C Weihs Data Analysis, Machine Learning and Knowledge Discovery, 333-341, 2014	1	2014
Piano and guitar tone distinction based on extended feature analysis M Eichhoff, I Vatolkin, C Weihs Classification and Data Mining, 215-224, 2013	1	2013
Software in music information retrieval C Weihs, K Friedrichs, M Eichhoff, I Vatolkin Challenges at the Interface of Data Analysis, Computer Science, and …, 2012	1	2012

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