Deep Learning Theory and Applications
Third International Conference, DeLTA 2022, Lisbon, Portugal, July 12-14, 2022, Revised Selected Papers
Published on 6. July 2023
IX, 121 pages
978-3-031-37317-6 (ISBN)
Description
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.
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.
More details
Series
Edition
1st ed. 2023
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
IX, 121 p. 49 illus., 47 illus. in color.
ISBN-13
978-3-031-37317-6 (9783031373176)
DOI
10.1007/978-3-031-37317-6
Schweitzer Classification
Other editions
Additional editions
Ana Fred | Carlo Sansone | Oleg Gusikhin
Deep Learning Theory and Applications
Third International Conference, DeLTA 2022, Lisbon, Portugal, July 12-14, 2022, Revised Selected Papers
Book
07/2023
Springer
€69.54
Shipment within 15-20 days
Content
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.
