Motahhir / Bossoufi Digital Technologies and Applications
1. Auflage 2024
ISBN: 978-3-031-68650-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Proceedings of ICDTA'24, Benguerir, Morocco, Volume 1
E-Book, Englisch, 571 Seiten
Reihe: Lecture Notes in Networks and Systems
ISBN: 978-3-031-68650-4
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book presents volume 1 of selected research papers presented at the fourth International Conference on Digital Technologies and Applications (ICDTA’24). Highlighting the latest innovations in digital technologies as: artificial intelligence, Internet of Things, embedded systems, chatbot, network technology, digital transformation and their applications in several areas as Industry 4.0, sustainability, energy transition, and healthcare, the book encourages and inspires researchers, industry professionals, and policymakers to put these methods into practice.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Exploring Arabic Hotel Reviews: Sentiment Insights through Deep Learning and BERT Transformers Models.- Unraveling the Intersection of Artificial Intelligence and Idea Generation A Systematic Literature Review.- Enhancing Student Success in Physical Education through Educational Data Mining Techniques.- A Fuzzy Timed Petri Net Approach to Modeling Forward Collision Warning Systems Based on the 3-Second Rule.- A systematic literature review on regression machine learning for urban flood hazard mapping.- Leveraging Artificial Intelligence for Environmental Information Integration in Investment Decision Making.- Leveraging deep collaborative filtering for advanced recommender systems.- Is AI an effective learning tool in academic writing Investigating the perceptions of third year university students on the use of artificial intelligence in classroom instruction.- Understanding the Attitude of Teacher Education Students toward Utilizing ChatGPT as a Learning Tool A Quantitative Analysis.- Machine Learning and Big Data for Cybersecurity systematic Literature Review.
