| Assessing the performance of a semi‐automated acoustic monitoring system for primates S Heinicke, AK Kalan, OJJ Wagner, R Mundry, H Lukashevich, HS Kühl Methods in Ecology and Evolution 6 (7), 753-763, 2015 | 124 | 2015 |
| Towards Quantitative Measures of Evaluating Song Segmentation. HM Lukashevich ISMIR, 375-380, 2008 | 86 | 2008 |
| Feature-based extraction of plucking and expression styles of the electric bass guitar J Abeßer, H Lukashevich, G Schuller 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 59 | 2010 |
| Using one-class SVM outliers detection for verification of collaboratively tagged image training sets H Lukashevich, S Nowak, P Dunker 2009 IEEE International Conference on Multimedia and Expo, 682-685, 2009 | 55 | 2009 |
| Performance measures for multilabel evaluation: a case study in the area of image classification S Nowak, H Lukashevich, P Dunker, S Rüger Proceedings of the international conference on Multimedia information …, 2010 | 50 | 2010 |
| Effective singing voice detection in popular music using arma filtering H Lukashevich, M Gruhne, C Dittmar Workshop on Digital Audio Effects (DAFx’07), 2007 | 40 | 2007 |
| Sounding industry: Challenges and datasets for industrial sound analysis S Grollmisch, J Abeßer, J Liebetrau, H Lukashevich 2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019 | 39 | 2019 |
| Acoustic Scene Classification by Combining Autoencoder-Based Dimensionality Reduction and Convolutional Neural Networks. J Abeßer, SI Mimilakis, R Gräfe, HM Lukashevich, I Fraunhofer DCASE, 7-11, 2017 | 33 | 2017 |
| From Multi-Labeling to Multi-Domain-Labeling: A Novel Two-Dimensional Approach to Music Genre Classification. HM Lukashevich, J Abeßer, C Dittmar, H Grossmann ISMIR, 459-464, 2009 | 32 | 2009 |
| A study on spoken language identification using deep neural networks A Draghici, J Abeßer, H Lukashevich Proceedings of the 15th International Conference on Audio Mostly, 253-256, 2020 | 24 | 2020 |
| A distributed sensor network for monitoring noise level and noise sources in urban environments J AbeBer, M Gotze, S Kuhnlenz, R Grafe, C Kuhn, T ClauB, ... 2018 IEEE 6th International Conference on Future Internet of Things and …, 2018 | 24 | 2018 |
| Multilabel classification evaluation using ontology information S Nowak, H Lukashevich Proceedings of ESWC Workshop on Inductive Reasoning and Machine Learning on …, 2009 | 23 | 2009 |
| Automatic classification of musical pieces into global cultural areas A Kruspe, H Lukashevich, J Abeßer, H Großmann, C Dittmar Audio Engineering Society Conference: 42nd International Conference …, 2011 | 21 | 2011 |
| Investigating CNN-based Instrument Family Recognition for Western Classical Music Recordings. M Taenzer, J Abeßer, SI Mimilakis, C Weiß, M Müller, H Lukashevich, ... ISMIR, 612-619, 2019 | 20 | 2019 |
| Classification of music genres based on repetitive basslines J Abeßer, H Lukashevich, P Bräuer Journal of New Music Research 41 (3), 239-257, 2012 | 17 | 2012 |
| Genre Classification Using Bass-Related High-Level Features and Playing Styles. J Abeßer, HM Lukashevich, C Dittmar, G Schuller ISMIR, 453-458, 2009 | 17 | 2009 |
| Music search and recommendation K Brandenburg, C Dittmar, M Gruhne, J Abeßer, H Lukashevich, P Dunker, ... Handbook of multimedia for digital entertainment and arts, 349-384, 2009 | 15 | 2009 |
| Plausible augmentation of auditory scenes using dynamic binaural synthesis for personalized auditory realities K Brandenburg, E Cano, F Klein, T Köllmer, H Lukashevich, A Neidhardt, ... Audio Engineering Society Conference: 2018 AES International Conference on …, 2018 | 13 | 2018 |
| Automatic speech/music discrimination for broadcast signals A Kruspe, D Zapf, H Lukashevich INFORMATIK 2017, 2017 | 12 | 2017 |
| Desed-fl and urban-fl: Federated learning datasets for sound event detection DS Johnson, W Lorenz, M Taenzer, S Mimilakis, S Grollmisch, J Abeßer, ... 2021 29th European Signal Processing Conference (EUSIPCO), 556-560, 2021 | 11 | 2021 |
