Collaborative city digital twin for the COVID-19 pandemic: A federated learning solution
The novel coronavirus, COVID-19, has caused a crisis that affects all segments of the
population. As the knowledge and understanding of COVID-19 evolve, an appropriate …
population. As the knowledge and understanding of COVID-19 evolve, an appropriate …
Extraction of descriptive driving patterns from driving data using unsupervised algorithms
Understanding drivers' behavioral characteristics is critical for the design of decision-making
modules in autonomous vehicles (AVs) and advanced driver assistance systems (ADASs) …
modules in autonomous vehicles (AVs) and advanced driver assistance systems (ADASs) …
SLAFusion: Attention fusion based on SAX and LSTM for dangerous driving behavior detection
Dangerous driving behaviors are the main cause of most traffic accidents, and the detection
of these behaviors is one of the extremely important researches in Intelligent Transportation …
of these behaviors is one of the extremely important researches in Intelligent Transportation …
Improving traffic safety through traffic accident risk assessment
Z Hu, J Zhou, E Zhang - Sustainability, 2023 - mdpi.com
The continuous development of sensors and the Internet of Things has produced a large
amount of traffic data with location information. The improvement of traffic safety benefits …
amount of traffic data with location information. The improvement of traffic safety benefits …
Multivariate time series forecasting with transfer entropy graph
Multivariate Time Series (MTS) forecasting is an essential problem in many fields. Accurate
forecasting results can effectively help in making decisions. To date, many MTS forecasting …
forecasting results can effectively help in making decisions. To date, many MTS forecasting …
Similarity measure based on incremental warping window for time series data mining
H Li, C Wang - IEEE Access, 2018 - ieeexplore.ieee.org
A similarity measure is one of the most important tasks in the fields of time series data
mining. Its quality often affects the efficiency and effectiveness of the related algorithms that …
mining. Its quality often affects the efficiency and effectiveness of the related algorithms that …
FedDAF: Federated deep attention fusion for dangerous driving behavior detection
Dangerous driving behavior detection is one of the most important researches in Intelligent
Transportation System (ITS), which can effectively reduce the probability and number of …
Transportation System (ITS), which can effectively reduce the probability and number of …
Residuals-based deep least square support vector machine with redundancy test based model selection to predict time series
Y Yu, J Li - Tsinghua Science and Technology, 2019 - ieeexplore.ieee.org
In this paper, we propose a novel Residuals-Based Deep Least Squares Support Vector
Machine (RBD-LSSVM). In the RBD-LSSVM, multiple LSSVMs are sequentially connected …
Machine (RBD-LSSVM). In the RBD-LSSVM, multiple LSSVMs are sequentially connected …
Collision Risk Assessment for Intelligent Vehicles Considering Multi-Dimensional Uncertainties
Z Gao, M Bao, T Cui, F Shi, X Chen, W Wen… - IEEE …, 2024 - ieeexplore.ieee.org
To ensure the reliability of autonomous driving, the system must be capable of potential
hazard identification and appropriate response to prevent accidents. This involves the …
hazard identification and appropriate response to prevent accidents. This involves the …
Fabric recognition using zero-shot learning
In this work, we use a deep learning method to tackle the Zero-Shot Learning (ZSL) problem
in tactile material recognition by incorporating the advanced semantic information into a …
in tactile material recognition by incorporating the advanced semantic information into a …