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1 Contributo su Rivista 33533
- 1.1 Articolo in rivista 30716
- 1.2 Recensione in rivista 630
- 1.3 Scheda bibliografica 57
- 1.4 Nota a sentenza 410
- 1.5 Abstract in rivista 1685
- 1.6 Traduzione in rivista 35

2 Contributo in Volume 10912
- 2.1 Contributo in volume (Capitolo o Saggio) 9880
- 2.2 Prefazione/Postfazione 284
- 2.3 Breve introduzione 114
- 2.4 Voce (in dizionario o enciclopedia) 535
- 2.5 Traduzione in volume 60
- 2.6 Recensione in volume 3
- 2.7 Schede di catalogo 36

3 Libro 2008
- 3.1 Monografia o trattato scientifico 1865
- 3.2 Concordanza 6
- 3.3 Indice 1
- 3.4 Bibliografia 4
- 3.5 Edizione critica 48
- 3.6 Pubblicazione di fonti inedite 15
- 3.7 Commento scientifico 22
- 3.8 Traduzione di libro 47

4 Contributo in Atti di Convegno (Proceeding) 14080
- 4.1 Contributo in Atti di convegno 9810
- 4.2 Abstract in Atti di convegno 3138
- 4.3 Poster 1132

5 Altro 746
- 5.01 Composizione 0
- 5.02 Disegno 0
- 5.03 Design 12
- 5.04 Performance 38
- 5.05 Esposizione 9
- 5.06 Mostra 36
- 5.07 Manufatto 0
- 5.08 Prototipo d'arte e relativi progetti 1
- 5.09 Cartografia 27
- 5.10 Banca dati 13
- 5.11 Software 4
- 5.12 Altro 579
- 5.13 Progetto architettonico 27

6 Brevetti 117
- 6.1 Brevetto 117

7 Curatele 955
- 7.1 Curatela 955

8 Tesi di dottorato 1349
- 8.1 Tesi di dottorato 77
- 8.2 Tesi di dottorato (ePrints) 1272

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Towards an Inadequately Rational Bicameralism. The Italian Senate “Reform” (1948-1963)

Quantitative extensions of reaction systems based on SOS semantics

The SoundLight System: Fostering Adaptive Sound and Light Control in Clinical Environment

From early biological models to CNNs: do they look where humans look?

Early hierarchical computational visual models as well as recent deep neural networks have been inspired by the functioning of the primate visual cortex system. Although much effort has been made to dissect neural networks to visualize the features they learn at the individual units, the scope of the visualizations has been limited to a categorization of the features in terms of their semantic level. Considering the ability humans have to select high semantic level regions of a scene, the que...

On the correlation between human fixations, handcrafted and CNN features

Traditional local image descriptors such as SIFT and SURF are based on processings similar to those that take place in the early visual cortex. Nowadays, convolutional neural networks still draw inspiration from the human vision system, integrating computational elements typical of higher visual cortical areas. Deep CNN's architectures are intrinsically hard to interpret, so much effort has been made to dissect them in order to understand which type of features they learn. However, considerin...

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