Items where Author is "Jansson, A."
Article
Veldman, J. 
ORCID: 0000-0001-8615-5844 & Jansson, A. (2020).
Planetary Boundaries and Corporate Reporting: The Role of the Conceptual Basis of the Corporation.
Accounting, Economics and Law: A Convivium, 10(2),
article number 20180037.
doi: 10.1515/ael-2018-0037
Jansson, A., Bittner, R. M., Ewert, S. & Weyde, T. ORCID: 0000-0001-8028-9905 (2019).
Joint singing voice separation and F0 estimation with deep U-net architectures.
2019 27th European Signal Processing Conference (EUSIPCO), 2019-S,
doi: 10.23919/EUSIPCO.2019.8902550
Conference or Workshop Item
Jansson, A., Humphrey, E., Montecchio, N. , Bittner, R., Kumar, A. & Weyde, T. ORCID: 0000-0001-8028-9905 (2017).
Singing voice separation with deep U-Net convolutional networks.
Paper presented at the 18th International Society for Music Information Retrieval Conference, 23-27 Oct 2017, Suzhou, China.
Benetos, E., Jansson, A. & Weyde, T. (2014). Improving automatic music transcription through key detection. In: Dittmar, C, Fazekas, G & Ewert, S (Eds.), http://www.aes.org/conferences/53/technical_programme.cfm. AES 53rd International Conference on Semantic Audio, 27 - 29 Jan 2014, London, UK.
Monograph
Collison, D., Jansson, A., Larsson-Olaison, U. , Power, D. M., Cooper, C., Gray, R., Ferguson, J., Sikka, P., Millo, Y., Jonnergård, K., Djelic, M-L., Quattrone, P., Cooper, D. J., Carter, C., Liew, P., Coles, R. F., Robson, K., Chabrak, N., Stevenson, L., Willmott, H. & Veldman, J. (2016). The Modern Corporation Statement on Accounting. London, UK: The Modern Corporation Project.
Thesis
Jansson, A. (2019). Musical source separation with deep learning and large-scale datasets. (Unpublished Doctoral thesis, City, University of London)