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
Seiten
2023
|
1st ed. 2023
Springer International Publishing (Verlag)
978-3-031-37319-0 (ISBN)
Springer International Publishing (Verlag)
978-3-031-37319-0 (ISBN)
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.
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.
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.
Erscheinungsdatum | 08.07.2023 |
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Reihe/Serie | Communications in Computer and Information Science |
Zusatzinfo | XI, 151 p. 71 illus., 51 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 260 g |
Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
Schlagworte | Big Data Analytics • computer vision • convolutional neural networks • Deep Hierarchical Networks • Deep Reinforcement Learning • Evolutionary Methods • generative adversarial networks • Graph representation learning • image classification • machine learning • Meta-Learning and Deep Networks • Models and Algorithms • Natural language understanding • Object detection • Recurrent Neural Network • semantic indexing |
ISBN-10 | 3-031-37319-7 / 3031373197 |
ISBN-13 | 978-3-031-37319-0 / 9783031373190 |
Zustand | Neuware |
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