Deep Learning Theory and Applications

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Details

This book constitutes the refereed post-conference proceedings of the Third International Conference on Deep Learning Theory and Applications, DeLTA 2022, held in Lisbon, Portugal, during January 17-18, 2022.

The 6 full papers included in this book were carefully reviewed and selected from 36 submissions. They present recent research on machine learning and artificial intelligence in real-world applications such as computer vision, information retrieval and summarization from structured and unstructured multimodal data sources, natural language understanding and translation, and many other application domains.

Inhalt
Modified SkipGram Negative Sampling Model for Faster Convergence of Graph Embedding.- Active Collection of Well-being and Health Data in Mobile Devices.- Reliable Classification of Images by Calculating Their Credibility using a Layer-wise Activation Cluster Analysis of CNNs.- Trac Sign Repositories: Bridging the Gap between Real and Synthetic Data.- Convolutional Neural Networks for Structural Damage Localization on Digital Twins.- Evaluating and Improving RoSELS for Road Surface Extraction from 3D Automotive LiDAR Point Cloud Sequences.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031373169
    • Genre Information Technology
    • Auflage 1st edition 2023
    • Editor Ana Fred, Kurosh Madani, Oleg Gusikhin, Carlo Sansone
    • Lesemotiv Verstehen
    • Anzahl Seiten 132
    • Größe H235mm x B155mm x T8mm
    • Jahr 2023
    • EAN 9783031373169
    • Format Kartonierter Einband
    • ISBN 3031373162
    • Veröffentlichung 07.07.2023
    • Titel Deep Learning Theory and Applications
    • Untertitel Third International Conference, DeLTA 2022, Lisbon, Portugal, July 12-14, 2022, Revised Selected Papers
    • Gewicht 213g
    • Herausgeber Springer Nature Switzerland
    • Sprache Englisch

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