| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNISALENTO991003950909707536 |
|
|
Titolo |
Da Raffaello a Balla : capolavori dell’Accademia Nazionale di San Luca / a cura di Vittorio Sgarbi |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Bard : Forte di Bard, 2017 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Descrizione fisica |
|
|
|
|
|
|
Collana |
|
|
|
|
|
|
Altri autori (Persone) |
|
|
|
|
|
|
Altri autori (Enti) |
|
Accademia Nazionale di San Luca |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
|
|
Soggetti |
|
Arte - Accademia Nazionale di San Luca - Cataloghi di esposizioni |
Accademia Nazionale di San Luca - Cataloghi |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Catalogo della Mostra tenuta a Bard nel 2017-2018 |
|
|
|
|
|
|
|
|
|
|
|
|
|
2. |
Record Nr. |
UNINA9910510426503321 |
|
|
Autore |
Schuller Björn W. |
|
|
Titolo |
Proceedings of the 2nd on Multimodal Sentiment Analysis Challenge : October 24, 2021, Virtual Event, China / / Björn W. Schuller [and four others] |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
New York : , : Association for Computing Machinery, , [2021] |
|
©2021 |
|
|
|
|
|
|
|
|
|
Descrizione fisica |
|
1 online resource (83 pages) : illustrations |
|
|
|
|
|
|
Collana |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Human-computer interaction |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Sommario/riassunto |
|
It is our great pleasure to welcome you to the 2nd Multimodal Sentiment Analysis Challenge and Workshop (MuSe 2021), held in conjunction with the ACM Multimedia 2021. The MuSe challenge and associated workshop continue to push the boundaries of integrated audio-visual and textual based sentiment analysis and emotion sensing. In its 2nd edition, we posed the problem of the prediction of continuous-valued dimensional affect in YouTube reviews and stress-induced scenarios. Further tasks were the classification of 5 artificially created arousal and valence classes, and the recognition of a fused physio-arousal signal also in a stressful situation. The mission of the MuSe Challenge and Workshop is to provide a common benchmark for individual multimodal information processing and to bring together the symbolic-based Sentiment Analysis and the signal-based Affective Computing communities, to compare the merits of multimodal fusion for the three core modalities under well-defined conditions. Another motivation is the need to advance sentiment and emotion recognition systems to be able to deal with unsegmented and previously unexplored naturalistic behaviour in large amounts of in-the-wild data, as this is exactly the type of data that we face in real life. As you will see, these goals have been reached with the selection of the data and |
|
|
|
|
|
|
|
|
|
|
the (challenge) contributions. |
|
|
|
|
|
| |