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 …
[HTML][HTML] Beyond encryption: Exploring the potential of physical layer security in UAV networks
Unmanned aerial vehicles (UAVs) have attracted much attention for civil and military uses
because of their high mobility and adaptable deployment capabilities in open spaces. They …
because of their high mobility and adaptable deployment capabilities in open spaces. They …
A new service composition method in the cloud‐based internet of things environment using a grey wolf optimization algorithm and MapReduce framework
Cloud computing is quickly becoming a common commercial model for software delivery
and services, enabling companies to save maintenance, infrastructure, and labor expenses …
and services, enabling companies to save maintenance, infrastructure, and labor expenses …
Multiheaded deep learning chatbot for increasing production and marketing
S Zheng, Z Yahya, L Wang, R Zhang… - Information Processing & …, 2023 - Elsevier
Some businesses on product development prefer to use a chatbot for judging the customer's
view. Today, the ability of a chatbot to consider the context is challenging due to its technical …
view. Today, the ability of a chatbot to consider the context is challenging due to its technical …
Vehicle recognition pipeline via DeepSort on aerial image datasets
Introduction Unmanned aerial vehicles (UAVs) are widely used in various computer vision
applications, especially in intelligent traffic monitoring, as they are agile and simplify …
applications, especially in intelligent traffic monitoring, as they are agile and simplify …
Vehicle detection and classification via YOLOv8 and deep belief network over aerial image sequences
Vehicle detection and classification are the most significant and challenging activities of an
intelligent traffic monitoring system. Traditional methods are highly computationally …
intelligent traffic monitoring system. Traditional methods are highly computationally …
Stackelberg game-based task offloading for joint service caching and resource allocation optimization in UAV-assisted VEC
C Li, L Yu, S Zeng, Y Zhang, K Jiang… - ACM Transactions on …, 2025 - dl.acm.org
The development of novel applications causes increased demands on the computational
capabilities of Vehicular Edge Computing (VEC). Current works have introduced Unmanned …
capabilities of Vehicular Edge Computing (VEC). Current works have introduced Unmanned …
Joint task offloading and resource allocation in aerial-terrestrial UAV networks with edge and fog computing for post-disaster rescue
Unmanned aerial vehicles (UAVs) are playing an increasingly important role in assisting fast-
response post-disaster rescue due to their fast deployment, flexible mobility, and low cost …
response post-disaster rescue due to their fast deployment, flexible mobility, and low cost …
Task offloading in Internet of Things based on the improved multi-objective aquila optimizer
Abstract The Internet of Things (IoT) is a network of tens of billions of physical devices that
are all connected to each other. These devices often have sensors or actuators, small …
are all connected to each other. These devices often have sensors or actuators, small …
Multi-objective optimization for multi-uav-assisted mobile edge computing
Recent developments in unmanned aerial vehicles (UAVs) and mobile edge computing
(MEC) have provided users with flexible and resilient computing services. However, meeting …
(MEC) have provided users with flexible and resilient computing services. However, meeting …