Deep Learning Theory and Applications: Third International Conference, DeLTA 2022, Lisbon, Portugal, July 12–14, 2022, Revised Selected Papers: Communications in Computer and Information Science, cartea 1858
Editat de Ana Fred, Carlo Sansone, Oleg Gusikhin, Kurosh Madanien Limba Engleză Paperback – 7 iul 2023
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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Specificații
ISBN-13: 9783031373169
ISBN-10: 3031373162
Ilustrații: IX, 121 p. 49 illus., 47 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.2 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Communications in Computer and Information Science
Locul publicării:Cham, Switzerland
ISBN-10: 3031373162
Ilustrații: IX, 121 p. 49 illus., 47 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.2 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Communications in Computer and Information Science
Locul publicării:Cham, Switzerland
Cuprins
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.