City Research Online

Items where Author is "Jansson, A."

Up a level
Export as [feed] RSS 2.0 [feed] RSS
Group by: Type | No Grouping
Number of items: 6.

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, 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. Paper presented at the 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., JonnergÄrd, 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 (Unpublished Doctoral thesis, City, University of London)

This list was generated on Thu Feb 9 04:02:44 2023 UTC.