Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Michele, Buccoli"'
Autor:
Luca Comanducci, Michele Buccoli, Massimiliano Zanoni, Augusto Sarti, Stefano Delle Monache, Giovanni Cospito, Enrico Pietrocola, Filippo Berbenni
Publikováno v:
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 602, Iss 23, Pp 119-127 (2018)
With the big improvement of digital communication networks, Networked Music Performances (NMP) received a great interest from music live performance and music recording industry. The positive impact of NMP in pedagogical appli- cations, instead, has
Externí odkaz:
https://doaj.org/article/bc2d227473524c7bb90ff2833ede2a9f
Autor:
Augusto Sarti, Karen Wood, Massimiliano Zanoni, Michele Buccoli, Rosemary (Rosa) Elizabeth Cisneros, Sarah Whatley
Publikováno v:
Body, Space & Technology Journal, Vol 18, Iss 1 (2019)
Virtual reality (VR) is becoming an increasingly intriguing space for dancers and choreographers. Choreographers may find new possibility emerging in using virtual reality to create movement and the WhoLoDancE: Whole-Body Interaction Learning for Dan
Externí odkaz:
https://doaj.org/article/db55c6299d5847d2a01f568e0dff7d9a
Autor:
Marco Olivieri, Luca Comanducci, Mirco Pezzoli, Davide Balsarri, Luca Menescardi, Michele Buccoli, Simone Pecorino, Antonio Grosso, Fabio Antonacci, Augusto Sarti
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94d630e3aab7cd7ac630fffe2e279edb
https://doi.org/10.1109/icassp49357.2023.10096891
https://doi.org/10.1109/icassp49357.2023.10096891
Autor:
Katerina El Raheb, Michele Buccoli, Massimiliano Zanoni, Akrivi Katifori, Aristotelis Kasomoulis, Augusto Sarti, Yannis Ioannidis
Publikováno v:
Multimedia Tools and Applications. 82:3363-3395
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c963341cbdc9ec7ffa37bbd4123b76ea
https://doi.org/10.1007/s11042-022-12602-y
https://doi.org/10.1007/s11042-022-12602-y
Publikováno v:
ARTECH
The evolution of technology in past few years highly influenced our daily life under many aspects. Very recently, the advent of more effective machine learning algorithms facilitated the explosion of the application of artificial intelligence in seve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cea481d08ac952282f15d43ed56c1a9
https://doi.org/10.1145/3359852.3359970
https://doi.org/10.1145/3359852.3359970
Publikováno v:
EUSIPCO
Nowadays, a great part of music consumption on music streaming services are based on playlists. Playlists are still mainly manually generated by expert curators, or users, process that in several cases is not a feasible with huge amount of music to d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e2a3180b1fc372f1e6d4dc7e2db918ef
https://doi.org/10.23919/eusipco.2019.8903002
https://doi.org/10.23919/eusipco.2019.8903002
Autor:
Massimiliano Zanoni, Stefano Cherubin, Augusto Sarti, Stefano Tubaro, Clara Borrelli, Michele Buccoli
Publikováno v:
2019 International Workshop on Multilayer Music Representation and Processing (MMRP).
The increased availability of musical content comes with the need of novel paradigms for recommendation, browsing and retrieval from large music libraries. Most music players and streaming services propose a paradigm based on content listing of meta-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2405443d87f221cd52675de1746f4bc1
https://doi.org/10.1109/mmrp.2019.00013
https://doi.org/10.1109/mmrp.2019.00013
Autor:
Dario G. Garao, Giacomo Verticale, Augusto Sarti, Massimiliano Zanoni, Cristina Rottondi, Michele Buccoli
Publikováno v:
ResearcherID
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::641153caebbbea952269e970e72afac8
https://doi.org/10.17743/jaes.2015.0074
https://doi.org/10.17743/jaes.2015.0074
Publikováno v:
2018 26th European Signal Processing Conference (EUSIPCO)
EUSIPCO
EUSIPCO
Deep learning networks have been successfully applied to solve a large number of tasks. The effectiveness of deep learning networks is limited by the amount and the variety of data used for the training. For this reason, deep-learning networks can be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b4a2ea0f2596122c52910478d9efa97