Deep learning challenges and prospects in wireless sensor network deployment
Y Qiu, L Ma, R Priyadarshi - Archives of Computational Methods in …, 2024 - Springer
This paper explores the transformative integration of deep learning applications in the
deployment of Wireless Sensor Networks (WSNs). As WSNs continue to play a pivotal role in …
deployment of Wireless Sensor Networks (WSNs). As WSNs continue to play a pivotal role in …
Efficiency and safety of traffic networks under the effect of autonomous vehicles
SM Hosseinian, H Mirzahossein - Iranian Journal of Science and …, 2023 - Springer
Efficiency and safety are two crucial aspects that have garnered significant attention in the
context of traffic networks. The investigation of autonomous vehicles (AVs) in terms of …
context of traffic networks. The investigation of autonomous vehicles (AVs) in terms of …
Anomaly diagnosis of connected autonomous vehicles: A survey
Connected autonomous vehicles (CAVs) are revolutionizing the development of
transportation due to their potential to improve transportation performance in many ways …
transportation due to their potential to improve transportation performance in many ways …
Enhanced abnormal data detection hybrid strategy based on heuristic and stochastic approaches for efficient patients rehabilitation
Over the last few years, substantial research has been conducted towards developing
efficient abnormal detection techniques while considering efficiency, accuracy, high …
efficient abnormal detection techniques while considering efficiency, accuracy, high …
[HTML][HTML] A Moving Metaverse: QoE challenges and standards requirements for immersive media consumption in autonomous vehicles
Abstract The evolution of Autonomous Vehicles (AVs) has blurred the distinction between
drivers and passengers, resulting in increased demand for in-car entertainment …
drivers and passengers, resulting in increased demand for in-car entertainment …
Remote intelligent perception system for multi-object detection
Introduction During the last few years, a heightened interest has been shown in classifying
scene images depicting diverse robotic environments. The surge in interest can be attributed …
scene images depicting diverse robotic environments. The surge in interest can be attributed …
An in-depth evaluation of deep learning-enabled adaptive approaches for detecting obstacles using sensor-fused data in autonomous vehicles
This paper delivers an exhaustive analysis of the fusion of multi-sensor technologies,
including traditional sensors such as cameras, Light Detection and Ranging (LiDAR), Radio …
including traditional sensors such as cameras, Light Detection and Ranging (LiDAR), Radio …
Transformer based composite network for autonomous driving trajectory prediction on multi-lane highways
In order to navigate through complex traffic scenarios safely and efficiently, the autonomous
vehicle (AV) predicts its own behavior and future trajectory based on the predicted …
vehicle (AV) predicts its own behavior and future trajectory based on the predicted …
Overtaking mechanisms based on augmented intelligence for autonomous driving: Datasets, methods, and challenges
V Chamola, A Chougule, A Sam… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
The field of autonomous driving research has made significant strides toward achieving full
automation, endowing vehicles with self-awareness and independent decision making …
automation, endowing vehicles with self-awareness and independent decision making …
Joint Task Offloading Based on Distributed Deep Reinforcement Learning-Based Genetic Optimization Algorithm for Internet of Vehicles
H Jin, YG Kim, Z Jin, C Fan, Y Xu - Journal of Grid Computing, 2024 - Springer
The growing number of individual vehicles and intelligent transportation systems have
accelerated the development of Internet of Vehicles (IoV) technologies. The Internet of …
accelerated the development of Internet of Vehicles (IoV) technologies. The Internet of …