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Deep Learning Theory and Applications [electronic resource] : Third International Conference, DeLTA 2022, Lisbon, Portugal, July 12–14, 2022, Revised Selected Papers /

Contributor(s): Material type: TextTextSeries: Communications in Computer and Information Science ; 1858Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023Description: IX, 121 p. 49 illus., 47 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031373176
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:
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.
In: Springer Nature eBookSummary: 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.
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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.

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.

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