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...
Gespeichert in:
| 1. Verfasser: | |
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| Weitere Verfasser: | , , |
| Format: | Livre numérique |
| Sprache: | Anglais |
| Veröffentlicht: |
London ; San Diego (Calif.) ; Cambridge (Mass.) :
Academic Press : Elsevier
2020.
Paris : Cyberlibris |
| Schlagworte: | |
| Online Zugang: | Accès Université d'Orléans et IFPM |
| Anmerkung: |
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 |
| LEADER | 04071nam a22003497a 4500 | ||
|---|---|---|---|
| 001 | 1287134 | ||
| 008 | 240917s2020 xxg ||| |||| 00| 0 eng d | ||
| 009 | PPN280308418 | ||
| 020 | |a 9780128232682 | ||
| 041 | 0 | |a eng | |
| 100 | 1 | |a Piuri, Vincenzo, |d 1960- | |
| 245 | 1 | 0 | |a Trends in deep learning methodologies : |b algorithms, applications, and systems |c edited by Vincenzo Piuri, Sandeep Raj, Angelo Genovese, Rajshree Srivastava. |
| 260 | |a London ; |a San Diego (Calif.) ; |a Cambridge (Mass.) : |b Academic Press : |b Elsevier. | ||
| 260 | |a Paris : |b Cyberlibris, |c 2020. | ||
| 500 | |a Couverture. https://static2.cyberlibris.com/books_upload/136pix/9780128232682.jpg | ||
| 500 | |a Cyberlibris (ScholarVox) corpus Informatique | ||
| 504 | |a Réf. bibliographiques en fin de chapitres. Index | ||
| 505 | 0 | |a 1. An introduction to deep learning applications in biometric recognition / Akash Dhiman ; Kanishk Gupta ; Deepak Kumar Sharma -- 2. Deep learning in big data and data mining / Deepak Kumar Sharma ; Bhanu Tokas ; Leo Adlakha -- 3. An overview of deep learning in big data, image, and signal processing in the modern digital age / Reinaldo Padilha França ; Ana Carolina Borges Monteiro et al -- 4. Predicting retweet class using deep learning / Amit Kumar Kushwaha ; Arpan Kumar Kar ; P. Vigneswara Ilavarasan -- 5. Role of the Internet of Things and deep learning for the growth of healthcare technology / Dinesh Bhatia ; S. Bagyaraj et al -- 6. Deep learning methodology proposal for the classification of erythrocytes and leukocytes / Ana Carolina Borges Monteiro ; Yuzo Iano et al -- 7. Dementia detection using the deep convolution neural network method / B. Janakiramaiah ; G. Kalyani -- 8. Deep similarity learning for disease prediction / Vagisha Gupta ; Shelly Sachdeva ; Neha Dohare -- 9. Changing the outlook of security and privacy with approaches to deep learning / Shweta Paliwal ; Vishal Bharti ; Amit Kumar Mishra -- 10. E-CART: an improved data stream mining approach / Pardeep Kumar -- 11. Deep learning-based detection and classification of adenocarcinoma cell nuclei / G. Kalyani ; B. Janakiramaiah -- 12. Segmentation and classification of hand symbol images using classifiers / Jatinder Kaur ; Nitin Mittal et al | |
| 506 | |a L'accès en ligne est réservé aux établissements ou bibliothèques ayant souscrit l'abonnement. Cyberlibris | ||
| 520 | |a "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 elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more | ||
| 650 | |a Traitement d'images | ||
| 650 | |a Traitement du signal | ||
| 650 | |a Santé | ||
| 650 | |a Intelligence artificielle en médecine | ||
| 650 | |a Apprentissage profond | ||
| 651 | |a Deep learning | ||
| 700 | 1 | |a Srivastava, Rajshree, |d 19..- |4 pbd | |
| 700 | 1 | |a Raj, Sandeep, |d 19..- |4 pbd | |
| 700 | 1 | |a Genovese, Angelo, |d 1985- |4 pbd | |
| 776 | 0 | |0 268649960 |t Trends in deep learning methodologies |o algorithms, applications, and systems |f edited by Vincenzo Piuri, Sandeep Raj, Angelo Genovese, Rajshree Srivastava |d 2021 |c London |n Academic Press |n Elsevier |p 1 vol. (XVII-288 p.) |s Hybrid computational intelligence for pattern analysis and understanding series |z 978-0-12-822226-3 | |
| 856 | 4 | |5 452349901:845630067 |u https://ezproxy.univ-orleans.fr/login?url=https://univ.scholarvox.com/book/88955535 |z Accès Université d'Orléans et IFPM | |
| 997 | |0 1287134 |1 Livre numérique |a Ressource numérique |b INSA |b ENSA |c 0/Bibliothèque numérique/ |c 1/Bibliothèque numérique/ScholarVox (ebooks)/ | ||