| Convolutional recurrent neural networks for music classification K Choi, G Fazekas, M Sandler, K Cho IEEE International conference on acoustics, speech and signal processing …, 2017 | 714 | 2017 |
| Automatic tagging using deep convolutional neural networks K Choi, G Fazekas, M Sandler 17th International Society for Music Information Retrieval (ISMIR …, 2016 | 472 | 2016 |
| Transfer learning for music classification and regression tasks K Choi, G Fazekas, M Sandler, K Cho 18th International Society for Music Information Retrieval Conference (ISMIR …, 2017 | 325 | 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, ... First International Conference on Technologies for Music Notation and …, 2015 | 192 | 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 | 173 | 2012 |
| Text-Based LSTM networks for Automatic Music Composition. K Choi, G Fazekas, M Sandler 1st Conference on Computer Simulation of Musical Creativity, 17 – 19 June …, 2016 | 162 | 2016 |
| A tutorial on deep learning for music information retrieval K Choi, G Fazekas, K Cho, M Sandler arXiv preprint arXiv:1709.04396, 2017 | 151 | 2017 |
| A comparison of audio signal preprocessing methods for deep neural networks on music tagging K Choi, G Fazekas, M Sandler, K Cho 26th European Signal Processing Conference (EUSIPCO), 1870-1874, 2018 | 93 | 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 | 82 | 2020 |
| SAFE: A system for extraction and retrieval of semantic audio descriptors R Stables, S Enderby, B De Man, G Fazekas, JD Reiss 15th International Society of Music Information Retrieval (ISMIR) Conference …, 2014 | 76 | 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 | 74 | 2023 |
| The Studio Ontology Framework. G Fazekas, MB Sandler ISMIR, 471-476, 2011 | 67 | 2011 |
| 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 | 66 | 2010 |
| Explaining deep convolutional neural networks on music classification K Choi, G Fazekas, M Sandler arXiv preprint arXiv:1607.02444, 2016 | 65 | 2016 |
| Open Multitrack Testbed B De Man, M Mora-Mcginity, G Fazekas, JD Reiss 37th Convention of the Audio Engineering Society, 7 Oct., Los Angeles, USA, 2014 | 62 | 2014 |
| The internet of musical things ontology L Turchet, F Antoniazzi, F Viola, F Giunchiglia, G Fazekas Journal of Web Semantics 60, 100548, 2020 | 59 | 2020 |
| Knowledge Representation Issues in Musical Instrument Ontology Design. S Kolozali, G Fazekas, M Barthet, MB Sandler ISMIR, 465-470, 2011 | 59 | 2011 |
| 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 |
| Contrastive audio-language learning for music I Manco, E Benetos, E Quinton, G Fazekas International Society for Music Information Retrieval (ISMIR), Bengaluru, India, 2022 | 55 | 2022 |
| MusCaps: Generating Captions for Music Audio I Manco, E Benetos, E Quinton, G Fazekas IEEE International Joint Conference on Neural Networks (IJCNN 2021), 2021 | 55 | 2021 |
Mark SandlerQueen Mary University of London在 qmul.ac.uk 的電子郵件地址已通過驗證
