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Deep learning theory and application...

International Conference on Deep Learning Theory and Applications (2020))

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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 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Deep learning theory and applications/ edited by Ana Fred, Carlo Sansone, Kurosh Madani.
其他題名:	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 /
其他題名:	DeLTA 2020
其他作者:	Fred, Ana.
團體作者:	International Conference on Deep Learning Theory and Applications
出版者:	Cham :Springer Nature Switzerland : : 2023.,
面頁冊數:	xi, 151 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Deep learning (Machine learning) - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-031-37320-6
ISBN:	9783031373206

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 /
Deep learning theory and applicationsfirst 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 /[electronic resource] :DeLTA 2020edited by Ana Fred, Carlo Sansone, Kurosh Madani. - Cham :Springer Nature Switzerland :2023. - xi, 151 p. :ill., digital ;24 cm. - Communications in computer and information science,18541865-0937 ;. - Communications in computer and information science ;1854..

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.

ISBN: 9783031373206

Standard No.: 10.1007/978-3-031-37320-6doiSubjects--Topical Terms:

3593062
Deep learning (Machine learning)
--Congresses.

LC Class. No.: Q325.73

Dewey Class. No.: 006.31

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 /
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