| Convolutional recurrent neural networks for music classification K Choi, G Fazekas, M Sandler, K Cho 2017 IEEE International conference on acoustics, speech and signal …, 2017 | 686 | 2017 |
| Automatic tagging using deep convolutional neural networks K Choi, G Fazekas, M Sandler arXiv preprint arXiv:1606.00298, 2016 | 464 | 2016 |
| Transfer learning for music classification and regression tasks K Choi, G Fazekas, M Sandler, K Cho arXiv preprint arXiv:1703.09179, 2017 | 320 | 2017 |
| Computer-aided melody note transcription using the Tony software: Accuracy and efficiency M Mauch, C Cannam, R Bittner, G Fazekas, J Salamon, J Dai, J Bello, ... | 189 | 2015 |
| Music emotion recognition: From content-to context-based models M Barthet, G Fazekas, M Sandler International Symposium on Computer Music Modeling and Retrieval, 228-252, 2012 | 172 | 2012 |
| Text-Based LSTM networks for Automatic Music Composition. K Choi, G Fazekas, M Sandler arXiv preprint arXiv:1604.05358, 2016 | 157 | 2016 |
| A tutorial on deep learning for music information retrieval K Choi, G Fazekas, K Cho, M Sandler arXiv preprint arXiv:1709.04396, 2017 | 147 | 2017 |
| A comparison of audio signal preprocessing methods for deep neural networks on music tagging K Choi, G Fazekas, M Sandler, K Cho 2018 26th European Signal Processing Conference (EUSIPCO), 1870-1874, 2018 | 89 | 2018 |
| The internet of audio things: State of the art, vision, and challenges L Turchet, G Fazekas, M Lagrange, HS Ghadikolaei, C Fischione IEEE internet of things journal 7 (10), 10233-10249, 2020 | 76 | 2020 |
| SAFE: A system for extraction and retrieval of semantic audio descriptors R Stables, S Enderby, B De Man, G Fazekas, JD Reiss | 75 | 2014 |
| The internet of sounds: Convergent trends, insights, and future directions L Turchet, M Lagrange, C Rottondi, G Fazekas, N Peters, J Østergaard, ... IEEE Internet of Things Journal 10 (13), 11264-11292, 2023 | 66 | 2023 |
| The Studio Ontology Framework. G Fazekas, MB Sandler ISMIR, 471-476, 2011 | 66 | 2011 |
| Explaining deep convolutional neural networks on music classification K Choi, G Fazekas, M Sandler arXiv preprint arXiv:1607.02444, 2016 | 65 | 2016 |
| An overview of semantic web activities in the OMRAS2 project G Fazekas, Y Raimond, K Jacobson, M Sandler Journal of New Music Research 39 (4), 295-311, 2010 | 65 | 2010 |
| Open Multitrack Testbed B De Man, M Mora-Mcginity, G Fazekas, JD Reiss AES Convention, 2014 | 60 | 2014 |
| The effects of noisy labels on deep convolutional neural networks for music tagging K Choi, G Fazekas, K Cho, M Sandler IEEE Transactions on Emerging Topics in Computational Intelligence 2 (2 …, 2018 | 58 | 2018 |
| Knowledge Representation Issues in Musical Instrument Ontology Design. S Kolozali, G Fazekas, M Barthet, MB Sandler ISMIR, 465-470, 2011 | 58 | 2011 |
| The internet of musical things ontology L Turchet, F Antoniazzi, F Viola, F Giunchiglia, G Fazekas Journal of Web Semantics 60, 100548, 2020 | 56 | 2020 |
| Towards a semantic architecture for the internet of musical things L Turchet, F Viola, G Fazekas, M Barthet 2018 23rd Conference of Open Innovations Association (FRUCT), 382-390, 2018 | 54 | 2018 |
| MusCaps: Generating Captions for Music Audio I Manco, E Benetos, E Quinton, G Fazekas IEEE International Joint Conference on Neural Networks (IJCNN 2021), 2021 | 50 | 2021 |
Mark SandlerQueen Mary University of Londonqmul.ac.uk의 이메일 확인됨