[PDF][PDF] Machine learning for smart environments in B5G networks: Connectivity and QoS
SH Alsamhi, FA Almalki, H Al-Dois… - Computational …, 2021 - downloads.hindawi.com
Review Article Machine Learning for Smart Environments in B5G Networks: Connectivity and
QoS Page 1 Review Article Machine Learning for Smart Environments in B5G Networks …
QoS Page 1 Review Article Machine Learning for Smart Environments in B5G Networks …
TIDE: Time-relevant deep reinforcement learning for routing optimization
Routing optimization has been researched in network design for a long time, and plenty of
optimization schemes have been proposed from both academia and industry. However …
optimization schemes have been proposed from both academia and industry. However …
Multi-path deep cnns for fine-grained car recognition
H Wang, J Peng, Y Zhao, X Fu - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Along with the growing demands of intelligent traffic system, how to recognize the category
information of a car from surveillance cameras has been an important task. Fine-grained car …
information of a car from surveillance cameras has been an important task. Fine-grained car …
Poisoning and evasion attacks against deep learning algorithms in autonomous vehicles
With the ongoing development and improvement of deep learning technology, autonomous
vehicles (AVs) have made tremendous progress in recent years. Despite its great potential …
vehicles (AVs) have made tremendous progress in recent years. Despite its great potential …
Deep learning-based sum data rate and energy efficiency optimization for MIMO-NOMA systems
The increasing demands for massive connectivity, low latency, and high reliability of future
communication networks require new techniques. Multiple-input-multiple-output non …
communication networks require new techniques. Multiple-input-multiple-output non …
[PDF][PDF] Technology prospect of 6G mobile communications
1. School of Information and Communication Engineering, Beijing University of Posts and
Telecommunications, Beijing 100876 2. Institute of Network Technology, Beijing University …
Telecommunications, Beijing 100876 2. Institute of Network Technology, Beijing University …
An intelligent route computation approach based on real-time deep learning strategy for software defined communication systems
Software Defined Networking (SDN) is regarded as the next generation paradigm as it
simplifies the structure of the data plane and improves the resource utilization. However, in …
simplifies the structure of the data plane and improves the resource utilization. However, in …
Consideration on automation of 5G network slicing with machine learning
VP Kafle, Y Fukushima, P Martinez-Julia… - … Learning for a 5G …, 2018 - ieeexplore.ieee.org
Machine learning has the capability to provide simpler solutions to complex problems by
analyzing a huge volume of data in a short time, learning for adapting its functionality to …
analyzing a huge volume of data in a short time, learning for adapting its functionality to …
Automatic modulation classification for MIMO systems via deep learning and zero-forcing equalization
Automatic modulation classification (AMC) is one of the most critical technologies for non-
cooperative communication systems. Recently, deep learning (DL) based AMC (DL-AMC) …
cooperative communication systems. Recently, deep learning (DL) based AMC (DL-AMC) …
DRSIR: A deep reinforcement learning approach for routing in software-defined networking
DM Casas-Velasco, OMC Rendon… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Traditional routing protocols employ limited information to make routing decisions, which
leads to slow adaptation to traffic variability and restricted support to the quality of service …
leads to slow adaptation to traffic variability and restricted support to the quality of service …