Catalogo Ricerca FBK

Catalogo Ricerca FBK: [19739] Home page macrotipologia

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1 Contributo su Rivista 8085
- 1.1 Articolo in rivista 7706
- 1.2 Recensione in rivista 259
- 1.3 Scheda bibliografica 1
- 1.4 Nota a sentenza 2
- 1.5 Abstract in rivista 74
- 1.6 Traduzione in rivista 43

2 Contributo in Volume 1690

3 Libro 299
- 3.1 Monografia o trattato scientifico 283
- 3.2 Concordanza 0
- 3.3 Indice 1
- 3.4 Bibliografia 4
- 3.5 Edizione critica 3
- 3.6 Pubblicazione di fonti inedite 0
- 3.7 Commento scientifico 0
- 3.8 Traduzione di libro 8

4 Contributo in Atti di Convegno (Proceeding) 8012
- 4.1 Contributo in Atti di convegno 7294
- 4.2 Abstract in Atti di convegno 417
- 4.3 Poster 301

5 Altro 1282
- 5.01 Composizione 0
- 5.02 Disegno 0
- 5.03 Design 0
- 5.04 Performance 0
- 5.05 Esposizione 0
- 5.06 Mostra 1
- 5.07 Manufatto 0
- 5.08 Prototipo d'arte e relativi progetti 1
- 5.09 Cartografia 0
- 5.10 Banca dati 8
- 5.11 Software 21
- 5.12 Altro 1251

6 Brevetti 71
- 6.1 Brevetto 71

7 Curatele 301
- 7.1 Curatela 301

Prodotti recenti

Large-scale structural controls on hot spring mineral deposits of geothermal systems (Mt. Amiata, Italy) highlighted by machine learning algorithms?

The cinnabar (±stibnite) deposits of the Mt. Amiata geothermal system and the associated hot springs and gas vents, occur along a N-S directed, narrow longitude region. In this study, we combine a geological and geophysical dataset gathered from the early stages of geothermal exploration of the district with a multivariate statistical analysis carried out by Machine Learning (ML) algorithms to highlight possible correlations between the distribution of the geothermal expressions of Mt. Amiat...

Listenable Maps for Audio Classifiers

Despite the impressive performance of deep learning models across diverse tasks, their complexity poses challenges for interpretation. This challenge is particularly evident for audio signals, where conveying interpretations becomes inherently difficult. To address this issue, we introduce Listenable Maps for Audio Classifiers (L-MAC), a posthoc interpretation method that generates faithful and listenable interpretations. L-MAC utilizes a decoder on top of a pretrained classifier to generate ...

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