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Autore: | Fred Ana |
Titolo: | Deep Learning Theory and Applications [[electronic resource] ] : First International Conference, DeLTA 2020, Virtual Event, July 8-10, 2020, and Second International Conference, DeLTA 2021, Virtual Event, July 7–9, 2021, Revised Selected Papers / / edited by Ana Fred, Carlo Sansone, Kurosh Madani |
Pubblicazione: | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
Edizione: | 1st ed. 2023. |
Descrizione fisica: | 1 online resource (163 pages) |
Disciplina: | 006.3 |
Soggetto topico: | Artificial intelligence |
Computer systems | |
Computer networks | |
Computer science—Mathematics | |
Artificial Intelligence | |
Computer System Implementation | |
Computer Communication Networks | |
Mathematics of Computing | |
Altri autori: | SansoneCarlo MadaniKurosh |
Nota di contenuto: | Alternative Data Augmentation for Industrial Monitoring using Adversarial Learning -- Multi-stage Conditional GAN Architectures for Person-image Generation -- Evaluating Deep Learning Models for the Automatic Inspection of Collective Protective Equipment -- Intercategorical Label Interpolation for Emotional Face Generation with Conditional Generative Adversarial Networks -- Forecasting the UN Sustainable Development Goals -- Disrupting Active Directory Attacks with Deep Learning for Organic Honeyuser Placement -- Crack Detection on Brick Walls by Convolutional Neural Networks using the Methods of Sub-Dataset Generation and Matching. |
Sommario/riassunto: | This book constitutes the refereed post-proceedings of the First International Conference and Second International Conference on Deep Learning Theory and Applications, DeLTA 2020 and DeLTA 2021, was held virtually due to the COVID-19 crisis on July 8-10, 2020 and July 7–9, 2021. The 7 full papers included in this book were carefully reviewed and selected from 58 submissions. They present recent research on machine learning and artificial intelligence in real-world applications such as computer vision, information retrieval and summarization from structuredand unstructured multimodal data sources, natural language understanding andtranslation, and many other application domains. |
Titolo autorizzato: | Deep Learning Theory and Applications |
ISBN: | 3-031-37320-0 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996546829503316 |
Lo trovi qui: | Univ. di Salerno |
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