Trends in deep learning methodologies : algorithms, applications, and systems
"Trends in deep learning methodologies [...] covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters el...
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| Auteur principal: | |
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| Autres auteurs: | , , |
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
London ; San Diego (Calif.) ; Cambridge (Mass.) :
Academic Press : Elsevier
2020.
Paris : Cyberlibris |
| Sujets: | |
| Accès en ligne: | Accès Université d'Orléans et IFPM |
| Note: |
Couverture. https://static2.cyberlibris.com/books_upload/136pix/9780128232682.jpg Cyberlibris (ScholarVox) corpus Informatique |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Trends in deep learning methodologies, algorithms, applications, and systems, edited by Vincenzo Piuri, Sandeep Raj, Angelo Genovese, Rajshree Srivastava, 2021, London, Academic Press, Elsevier, 1 vol. (XVII-288 p.), Hybrid computational intelligence for pattern analysis and understanding series, 978-0-12-822226-3 |