Graph representation learning and its applications: a survey
Graphs are data structures that effectively represent relational data in the real world. Graph
representation learning is a significant task since it could facilitate various downstream …
representation learning is a significant task since it could facilitate various downstream …
How to ensure the confidentiality of electronic medical records on the cloud: A technical perspective
Z Wu, S Xuan, J **e, C Lin, C Lu - Computers in biology and medicine, 2022 - Elsevier
From a technical perspective, for electronic medical records (EMR), this paper proposes an
effective confidential management solution on the cloud, whose basic idea is to deploy a …
effective confidential management solution on the cloud, whose basic idea is to deploy a …
Apple leaf disease recognition method with improved residual network
H Yu, X Cheng, C Chen, AA Heidari, J Liu, Z Cai… - Multimedia Tools and …, 2022 - Springer
The occurrence of apple diseases has dramatically affected the quality and yield of apples.
Disease monitoring is an important measure to ensure the healthy development of the apple …
Disease monitoring is an important measure to ensure the healthy development of the apple …
Multi-agent DRL for joint completion delay and energy consumption with queuing theory in MEC-based IIoT
G Wu, Z Xu, H Zhang, S Shen, S Yu - Journal of Parallel and Distributed …, 2023 - Elsevier
Abstract In the Industrial Internet of Things (IIoT), there exist numerous sensor devices with
weak computing power and small energy storage. To meet the real-time and big data …
weak computing power and small energy storage. To meet the real-time and big data …
Subgraph neural networks
Deep learning methods for graphs achieve remarkable performance on many node-level
and graph-level prediction tasks. However, despite the proliferation of the methods and their …
and graph-level prediction tasks. However, despite the proliferation of the methods and their …
FDSA-STG: Fully dynamic self-attention spatio-temporal graph networks for intelligent traffic flow prediction
Y Duan, N Chen, S Shen, P Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the development of transportation and the ever-improving of vehicular technology,
Artificial Intelligence (AI) has been popularized in Intelligent Transportation Systems (ITS) …
Artificial Intelligence (AI) has been popularized in Intelligent Transportation Systems (ITS) …
A basic framework for privacy protection in personalized information retrieval: An effective framework for user privacy protection
Z Wu, S Shen, H Li, H Zhou, C Lu - Journal of Organizational and …, 2021 - igi-global.com
Personalized information retrieval is an effective tool to solve the problem of information
overload. Along with the rapid development of emerging network technologies such as …
overload. Along with the rapid development of emerging network technologies such as …
Incorporating distributed DRL into storage resource optimization of space-air-ground integrated wireless communication network
Space-air-ground integrated network (SAGIN) is a new type of wireless network mode. The
effective management of SAGIN resources is a prerequisite for high-reliability …
effective management of SAGIN resources is a prerequisite for high-reliability …
A confusion method for the protection of user topic privacy in Chinese keyword-based book retrieval
In this article, aiming at a Chinese keyword-based book search service, from a technological
perspective, we propose to modify a user query sequence carefully to confuse the user …
perspective, we propose to modify a user query sequence carefully to confuse the user …
DTP-Net: A convolutional neural network model to predict threshold for localizing the lesions on dermatological macro-images
Highly focused images of skin captured with ordinary cameras, called macro-images, are
extensively used in dermatology. Being highly focused views, the macro-images contain …
extensively used in dermatology. Being highly focused views, the macro-images contain …