| Evaluation of feature extractors and psycho-acoustic transformations for music genre classification T Lidy, A Rauber ISMIR, 34-41, 2005 | 345 | 2005 |
| Experimenting with musically motivated convolutional neural networks J Pons, T Lidy, X Serra 2016 14th international workshop on content-based multimedia indexing (CBMI …, 2016 | 205 | 2016 |
| Structured visual markers for indoor pathfinding M Kalkusch, T Lidy, N Knapp, G Reitmayr, H Kaufmann, D Schmalstieg The First IEEE International Workshop Agumented Reality Toolkit,, 8 pp., 2002 | 179 | 2002 |
| CQT-based Convolutional Neural Networks for Audio Scene Classification. T Lidy, A Schindler DCASE, 60-64, 2016 | 131 | 2016 |
| Improving Genre Classification by Combination of Audio and Symbolic Descriptors Using a Transcription Systems. T Lidy, A Rauber, A Pertusa, JMI Quereda ISMIR, 61-66, 2007 | 114 | 2007 |
| On the suitability of state-of-the-art music information retrieval methods for analyzing, categorizing and accessing non-western and ethnic music collections T Lidy, CN Silla Jr, O Cornelis, F Gouyon, A Rauber, CAA Kaestner, ... Signal Processing 90 (4), 1032-1048, 2010 | 83 | 2010 |
| Comparing Shallow versus Deep Neural Network Architectures for Automatic Music Genre Classification. A Schindler, T Lidy, A Rauber FMT, 17-21, 2016 | 65 | 2016 |
| Parallel convolutional neural networks for music genre and mood classification T Lidy, A Schindler MIREX2016 3, 2016 | 58 | 2016 |
| Automatic audio segmentation: Segment boundary and structure detection in popular music E Peiszer, T Lidy, A Rauber Proc. of LSAS 106, 45-59, 2008 | 50 | 2008 |
| Mean-field model for the growth and coarsening of stoichiometric precipitates at grain boundaries E Kozeschnik, J Svoboda, R Radis, FD Fischer Modelling and simulation in materials science and engineering 18 (1), 015011, 2009 | 47 | 2009 |
| DelosDLMS-the integrated DELOS digital library management system M Agosti, S Berretti, G Brettlecker, A Del Bimbo, N Ferro, N Fuhr, D Keim, ... Digital Libraries: Research and Development: First International DELOS …, 2007 | 35 | 2007 |
| Combining audio and symbolic descriptors for music classification from audio T Lidy, A Rauber, A Pertusa, J Inesta Music Information Retrieval Information Exchange (MIREX), 2007 | 33 | 2007 |
| A multi-modal deep neural network approach to bird-song identification B Fazeka, A Schindler, T Lidy, A Rauber arXiv preprint arXiv:1811.04448, 2018 | 31 | 2018 |
| Fashion and apparel classification using convolutional neural networks A Schindler, T Lidy, S Karner, M Hecker arXiv preprint arXiv:1811.04374, 2018 | 30 | 2018 |
| Method and system to organize and visualize media T Lidy, W Jochum, E Peiszer US Patent App. 13/808,484, 2013 | 27 | 2013 |
| Automatic audio segmentation: Segment boundary and structure detection in popular music E Peiszer Technische Universität Wien, 2007 | 27 | 2007 |
| The map of mozart R Mayer, T Lidy, A Rauber na, 2006 | 26 | 2006 |
| Content-based organization of digital audio collections R Neumayer, T Lidy, A Rauber na, 2005 | 25 | 2005 |
| A cartesian ensemble of feature subspace classifiers for music categorization T Lidy, R Mayer, A Rauber, PJ Ponce de León Amador, A Pertusa, ... International Society for Music Information Retrieval, 2010 | 24 | 2010 |
| Evaluation of new audio features and their utilization in novel music retrieval applications T Lidy | 21 | 2006 |
