Buch, Englisch, Band 1267, 280 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 452 g
Proceedings of the 8th International Symposium, MISC 2024, Tamanghasset, Algeria, December 1-3, 2024
Buch, Englisch, Band 1267, 280 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 452 g
Reihe: Lecture Notes in Networks and Systems
ISBN: 978-3-031-82111-0
Verlag: Springer Nature Switzerland
This book offers a cutting-edge exploration of key advancements in artificial intelligence, IoT, data science, and their transformative impact on industries, particularly health care, in a rapidly evolving technological landscape. Readers will discover how AI and machine learning drive innovations, from detecting anomalies in satellite systems to enhancing medical diagnostics and treatment precision.
With a focus on real-world applications, the book delves into the integration of IoT systems and cloud computing to streamline business operations and improve efficiency. It also introduces groundbreaking data science techniques for analysis and prediction, making it a valuable resource for professionals, researchers, and students.
Designed for those looking to understand and harness the power of modern technology, this book provides insights that are both practical and forward-looking, equipping readers to address today’s challenges and shape the future.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Kybernetik, Systemtheorie, Komplexe Systeme
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Regelungstechnik
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
Weitere Infos & Material
Supervised ML-based Multi-Criteria For Detecting Malicious Nodes in FANET.- A semi-decentralized congestion-free multi-path energy routing for P2P energy trading systems.- Privacy-Preserving Intrusion Detection using FedSplit Learning.- Unveiling Human Activity Patterns in Smart Cities through a CNN-LSTM Approach.- Material Property Prediction with CNN-LSTM Hybrid Models and Periodic Table as Input Representation.- A Combined MaskRCNN-Watershed Model for Colorectal Gland Segmentation from Histological Images.
