A survey on privacy-preserving control and filtering of networked control systems

Wang, Wei; Ma, Lifeng; Rui, Qiangqiang; Gao, Chen

doi:10.1080/00207721.2024.2343734

International Journal of Systems Science

2024

DOI: 10.1080/00207721.2024.2343734

|View full text |Cite

A survey on privacy-preserving control and filtering of networked control systems

Wei Wang,

Lifeng Ma,

Qiangqiang Rui

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

2025

Publication Types

Select...

Article5

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 5 publications

References 125 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A Novel Depth-Connected Region-Based Convolutional Neural Network for Small Defect Detection in Additive Manufacturing

Wang,

Liu

et al. 2024

Cogn Comput

View full text Add to dashboard Cite

Defect detection on the computed tomography (CT) images plays an important role in the development of metallic additive manufacturing (AM). Although some deep learning techniques have been adopted in the CT image-based defect detection problem, it is still a challenging task to accurately detect small-size defects in the presence of undesirable noises. In this paper, a novel defect detection method, namely, the depth-connected region-based convolutional neural network (DC-RCNN), is proposed to detect small defects and reduce the influence of noises. In particular, a saliency-guided region proposal method is first developed to generate small-size region proposals with the aim to accommodate the small defects. Then, the main architecture of DC-RCNN is proposed to extract and connect the consistent features across multiple frames, thereby reducing the influence of randomly distributed noises. Moreover, the transfer learning technique is utilized to improve the generalization ability of the proposed DC-RCNN. In order to verify the effectiveness and superiority, the proposed method is applied to the real-world AM data for defect detection. The experimental validations show that the proposed DC-RCNN is able to detect the small-size defects under noises and outperforms the original RCNN method in terms of detection accuracy and running time.

show abstract

A Novel Depth-Connected Region-Based Convolutional Neural Network for Small Defect Detection in Additive Manufacturing

Wang,

Liu

et al. 2024

Cogn Comput

View full text Add to dashboard Cite

show abstract

Privacy-preserving anomaly detection in stochastic dynamical systems: Synthesis of optimal Gaussian mechanisms

Hayati,

Murguia,

van de Wouw

2025

European Journal of Control

View full text Add to dashboard Cite

Stubborn state estimation for time-delay systems with relay communication network: The half-duplex case

Le,

Shen,

Zou

et al. 2024

Journal of the Franklin Institute

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A survey on privacy-preserving control and filtering of networked control systems

Cited by 5 publications

References 125 publications

A Novel Depth-Connected Region-Based Convolutional Neural Network for Small Defect Detection in Additive Manufacturing

A Novel Depth-Connected Region-Based Convolutional Neural Network for Small Defect Detection in Additive Manufacturing

Privacy-preserving anomaly detection in stochastic dynamical systems: Synthesis of optimal Gaussian mechanisms

Stubborn state estimation for time-delay systems with relay communication network: The half-duplex case

Contact Info

Product

Resources

About