Cargando…
Deep Learning-Based Adaptive Compression and Anomaly Detection for Smart B5G Use Cases Operation
The evolution towards next-generation Beyond 5G (B5G) networks will require not only innovation in transport technologies but also the adoption of smarter, more efficient operations of the use cases that are foreseen to be the high consumers of network resources in the next decades. Among different...
Autores principales: | El Sayed, Ahmad, Ruiz, Marc, Harb, Hassan, Velasco, Luis |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9861281/ https://www.ncbi.nlm.nih.gov/pubmed/36679840 http://dx.doi.org/10.3390/s23021043 |
Ejemplares similares
-
A Smart-Anomaly-Detection System for Industrial Machines Based on Feature Autoencoder and Deep Learning
por: Ahmed, Imran, et al.
Publicado: (2023) -
Anomaly detection with Deep Learning
por: Raval, Siraj
Publicado: (2017) -
Packet Flow Capacity Autonomous Operation Based on Reinforcement Learning
por: Barzegar, Sima, et al.
Publicado: (2021) -
Operator compression with deep neural networks
por: Kröpfl, Fabian, et al.
Publicado: (2022) -
The Deep Learning Solutions on Lossless Compression Methods for Alleviating Data Load on IoT Nodes in Smart Cities
por: Nasif, Ammar, et al.
Publicado: (2021)