Deep Learning Theory and Applications (eBook, PDF)
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 Redaktion: Fred, Ana; Madani, Kurosh; Sansone, Carlo
Deep Learning Theory and Applications (eBook, PDF)
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 Redaktion: Fred, Ana; Madani, Kurosh; Sansone, Carlo
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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…mehr
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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Inhaltsangabe
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.
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.
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