Buch, Englisch, Band 1740, 205 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 359 g
14th International Conference, ICT Innovations 2022, Skopje, Macedonia, September 29 - October 1, 2022, Proceedings
Buch, Englisch, Band 1740, 205 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 359 g
Reihe: Communications in Computer and Information Science
ISBN: 978-3-031-22791-2
Verlag: Springer Nature Switzerland
The 14 full papers and 1 short papers included in this book were carefully reviewed and selected from 42 submissions. They were organized in topical sections as follows: theoretical foundations and distributed computing; artificial intelligence and deep learning; applied artificial intelligence; education; and medical informatics.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
The New Normal: Innovative Informal Digital Learning after the Pandemic.- Theoretical foundations and distributed computing.- StegIm: Image in Image Steganography.- A Property of an Error-Detecting Code Based on Quasigroups.- Multi-access edge computing smart relocation approach from an NFV perspective.- Artificial intelligence and deep learning.- MACEDONIZER - The Macedonian Transformer Language Model.- Deep learning-based sentiment classification of social network texts in Amharic language.- Using centrality measures to extract knowledge from cryptocurrencies’ interdependencies networks.- Applied artificial intelligence.- Evaluating micro frontend approaches for code reusability.- Combining Static and Dynamic Features to Improve Longitudinal Image Retrieval for Alzheimer's Disease.- Architecture for collecting and analysing data from sensor devices.- Education.- Adapting a Web 2.0-basedCourse to a Fully Online Course and Readapting it Back for Face-to-Face Use.- Challenges and opportunities for women studying STEM.- Medical informatics.- Novel Methodology for Improving the Generalization Capability of Chemo-Informatics Deep Learning Models.- An exploration of Autism Spectrum Disorder classification from structural and functional MRI images.- Detection of High Noise Levels in Electrocardiograms.