George Fazekas

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Mark SandlerQueen Mary University of LondonVerified email at qmul.ac.uk
Mathieu BarthetSenior Lecturer in Digital Media, Queen Mary University of LondonVerified email at qmul.ac.uk
Keunwoo ChoiPrescient Design, GenentechVerified email at gene.com
Thomas WilmeringQueen Mary University of LondonVerified email at qmul.ac.uk
Simon DixonCentre for Digital Music, Queen Mary University of LondonVerified email at qmul.ac.uk
Kyunghyun ChoNew York University, GenentechVerified email at nyu.edu
Luca TurchetAssociate Professor, Dept. of Information Engineering and Computer Science, University of TrentoVerified email at unitn.it
Geraint WigginsProfessor of Computational Creativity, Vrije Universiteit Brussel / Queen Mary University of LondonVerified email at vub.ac.be
Joshua D. Reissqueen mary university of londonVerified email at qmul.ac.uk
Charalampos SaitisQueen Mary University of LondonVerified email at qmul.ac.uk
Beici LiangNOMONOVerified email at nomono.co
Şefki KolozaliLecturer in Embedded and Intelligent Systems, University of EssexVerified email at essex.ac.uk
Florian ThalmannKyoto UniversityVerified email at umn.edu
Matthias MauchApple, LondonVerified email at apple.com
Brecht De ManHead of Research, PXL-MusicVerified email at pxl.be
Johan PauwelsQueen Mary University of LondonVerified email at qmul.ac.uk
Mathieu LagrangeCNRS Researcher @ ls2nVerified email at ls2n.fr
Emmanouil BenetosQueen Mary University of London / The Alan Turing InstituteVerified email at qmul.ac.uk
Carlo FischioneProfessor, KTH, EECS, Network and Systems EngineeringVerified email at kth.se
Ben HayesQueen Mary University of LondonVerified email at qmul.ac.uk

George Fazekas

Queen Mary University of London

Verified email at qmul.ac.uk - Homepage

semantic audio music information retrieval semantic web music emotion recognition deep learning


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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	607	2017
Automatic tagging using deep convolutional neural networks K Choi, G Fazekas, M Sandler arXiv preprint arXiv:1606.00298, 2016	405	2016
Transfer learning for music classification and regression tasks K Choi, G Fazekas, M Sandler, K Cho arXiv preprint arXiv:1703.09179, 2017	276	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, ...	163	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	160	2012
Text-Based LSTM networks for Automatic Music Composition. K Choi, G Fazekas, M Sandler arXiv preprint arXiv:1604.05358, 2016	133	2016
A tutorial on deep learning for music information retrieval K Choi, G Fazekas, K Cho, M Sandler arXiv preprint arXiv:1709.04396, 2017	123	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	76	2018
SAFE: A system for extraction and retrieval of semantic audio descriptors R Stables, S Enderby, B De Man, G Fazekas, JD Reiss	72	2014
The Studio Ontology Framework. G Fazekas, MB Sandler ISMIR, 471-476, 2011	65	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	64	2010
Knowledge Representation Issues in Musical Instrument Ontology Design. S Kolozali, G Fazekas, M Barthet, MB Sandler ISMIR, 465-470, 2011	57	2011
Explaining deep convolutional neural networks on music classification K Choi, G Fazekas, M Sandler arXiv preprint arXiv:1607.02444, 2016	56	2016
Open Multitrack Testbed B De Man, M Mora-Mcginity, G Fazekas, JD Reiss AES Convention, 2014	54	2014
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	53	2020
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	52	2018
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	49	2018
The internet of musical things ontology L Turchet, F Antoniazzi, F Viola, F Giunchiglia, G Fazekas Journal of Web Semantics 60, 100548, 2020	48	2020
An Ontology for Audio Features. A Allik, G Fazekas, MB Sandler ISMIR, 73-79, 2016	45	2016
Genre-adaptive semantic computing and audio-based modelling for music mood annotation P Saari, G Fazekas, T Eerola, M Barthet, O Lartillot, M Sandler IEEE Transactions on Affective Computing 7 (2), 122-135, 2015	41	2015

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