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Article
Automation & Control Systems
Chunhua Hu et al.
Summary: This article proposes a digital twin-assisted real-time traffic data prediction method, which analyzes the traffic flow and velocity data monitored by IoV sensors and transmitted through 5G to optimize traffic scheduling and alleviate traffic jams.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Zhi Tian et al.
Summary: FCOS is a fully convolutional one-stage object detector that is anchor box free and achieves higher detection accuracy through post-processing non-maximum suppression.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Automation & Control Systems
Xiaokang Zhou et al.
Summary: This article proposes a few-shot learning model with Siamese convolutional neural network (FSL-SCNN) to enhance the accuracy of intelligent anomaly detection in industrial cyber-physical systems by alleviating over-fitting issues. Experimental results demonstrate that the proposed model can significantly improve the false alarm rate (FAR) and F1 scores in detecting intrusion signals for industrial CPS security protection.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Information Systems
Xiaokang Zhou et al.
Summary: This study focuses on multitarget detection for real-time surveillance in smart IoT systems. A newly designed deep neural network model called A-YONet, which combines the advantages of YOLO and MTCNN, is proposed for lightweight training and feature learning in an end-edge-cloud surveillance system. An intelligent detection algorithm is developed based on a preadjusting scheme of anchor box and a multilevel feature fusion mechanism. Experiments show the effectiveness of the proposed method in enhancing training efficiency and detection precision, especially for multitarget detection in smart IoT applications.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Biochemical Research Methods
Xiaokang Zhou et al.
Summary: This article discusses how the rapidly developed Health 2.0 technology has provided new solutions for online medical consultation and pre-diagnosis through the use of neural network-based models. By extracting and analyzing patient-physician generated data, this approach aims to guide patients' medical decision making process effectively in the era of Health 2.0.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Youssef Nait Malek et al.
Summary: This study introduced a speed forecasting method based on LSTM and found that the multivariate model outperformed the univariate model in short- and long-term forecasting, potentially improving the accuracy of vehicle speed prediction.
BIG DATA MINING AND ANALYTICS
(2021)
Article
Computer Science, Artificial Intelligence
Azidine Guezzaz et al.
Summary: The study focuses on modeling and validating a heterogeneous traffic classifier for categorizing collected events within networks, aiming to address vulnerabilities in intrusion detection systems during the analysis and classification of data activities.
BIG DATA MINING AND ANALYTICS
(2021)
Article
Computer Science, Artificial Intelligence
Hei Law et al.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2020)
