Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Domain Adaptation in Computer Vision with Deep Learning / Hemanth Venkateswara, Sethuraman Panchanathan editors
| Domain Adaptation in Computer Vision with Deep Learning / Hemanth Venkateswara, Sethuraman Panchanathan editors |
| Pubbl/distr/stampa | Cham, : Springer, 2020 |
| Descrizione fisica | xi, 256 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
94-XX - Information and communication theory, circuits [MSC 2020] 68Txx - Artificial intelligence [MSC 2020] |
| Soggetto non controllato |
Adversarial learning
Deep Learning Domain Confusion Domain adaptation Domain shift Feature alignment Generative models Hashing Image translation Lifelong Learning Maximum mean discrepancy Multitask Learning Spectral methods Transfer learning Zero-Shot Learning |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0249047 |
| Cham, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Generative Adversarial Networks for Image Generation / Xudong Mao, Qing Li
| Generative Adversarial Networks for Image Generation / Xudong Mao, Qing Li |
| Autore | Mao, Xudong |
| Pubbl/distr/stampa | Singapore, : Springer, 2021 |
| Descrizione fisica | xii, 77 p. : ill. ; 24 cm |
| Altri autori (Persone) | Li, Qing |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
68T07 - Artificial neural networks and deep learning [MSC 2020] |
| Soggetto non controllato |
Adversarial Networks
Deep Learning Generative Adversarial Networks Generative models Image Generation Image to Image Translation Machine learning Neural networks Unsupervised Domain Adaptation |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0275456 |
Mao, Xudong
|
||
| Singapore, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||