Cantitate/Preț
Produs

Deep Learning Theory and Applications: Communications in Computer and Information Science, cartea 1858

Editat de Ana Fred, Carlo Sansone, Oleg Gusikhin, Kurosh Madani
en 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.
Citește tot Restrânge

Din seria Communications in Computer and Information Science

Preț: 40294 lei

Preț vechi: 50367 lei
-20%

Puncte Express: 604

Carte tipărită la comandă

Livrare economică 09-23 iulie

Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit pentru acest produs Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.

Specificații

ISBN-13: 9783031373169
ISBN-10: 3031373162
Pagini: 132
Ilustrații: IX, 121 p. 49 illus., 47 illus. in color.
Dimensiuni: 155 x 235 x 8 mm
Greutate: 0.21 kg
Ediția:1st edition 2023
Editura: Springer
Colecția Communications in Computer and Information Science
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.