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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 /

Contributor(s): Material type: TextTextSeries: Communications in Computer and Information Science ; 1854Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023Description: XI, 151 p. 71 illus., 51 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031373206
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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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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.

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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