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Deep Learning Theory and Applications: 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 de Ana Fred

Deep Learning Theory and Applications: 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: Communications in Computer and Information Science, cartea 1854

Editat de Ana Fred, Carlo Sansone, Kurosh Madani
en Limba Engleză Paperback – 7 iul 2023
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.
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Specificații

ISBN-13: 9783031373190
ISBN-10: 3031373197
Ilustrații: XI, 151 p. 71 illus., 51 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.24 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Communications in Computer and Information Science

Locul publicării:Cham, Switzerland

Cuprins

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.