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Cyber-physical systems : intelligent models and algorithms / Alla G. Kravets, Alexander A. Bolshakov, Maxim Shcherbakov, editors.

9783030951160 (electronic bk.)
3030951162 (electronic bk.)
9783030951153 (print)
3030951154

Cham, Switzerland : Springer, 2022.

English

1 online resource (ix, 279 pages) : illustrations (some color).

10.1007/978-3-030-95116-0 doi

TJ213

006.2/2

This book is devoted to intelligent models and algorithms as the core components of cyber-physical systems. The complexity of cyber-physical systems developing and deploying requires new approaches to its modelling and design. Presents results in the field of modelling technologies that leverage the exploitation of artificial intelligence, including artificial general intelligence (AGI) and weak artificial intelligence. Provides scientific, practical, and methodological approaches based on bio-inspired methods, fuzzy models and algorithms, predictive modelling, computer vision and image processing. The target audience of the book are practitioners, enterprises representatives, scientists, PhD and Master students who perform scientific research or applications of intelligent models and algorithms in cyber-physical systems for various domains.

References -- Computer Vision and Image Processing -- Application of Computer Vision Tools to Create a System for Monitoring the Work of Ground Equipment in Open Pits of Gold Mining Enterprises -- 1 Introduction -- 2 Methods and Materials -- 2.1 Research Technology of Mining -- 2.2 Computer Vision Tasks -- 2.3 Materials -- 3 Results -- 3.1 Learning Outcomes of the Neural Network -- 3.2 Accuracy Metric Results -- 3.3 Results of Model Operation on the Test Site -- 4 Discussion -- References -- Framework for Biometric User Authentication Based on a Dynamic Handwritten Signature -- 1 Introduction -- 2 Background -- 2.1 Characteristics of a Dynamic Handwritten Signature -- 2.2 Basic Challenges -- 3 The Architecture of the Developed Framework -- 4 Experimental Research -- 4.1 Selection of the Parameters -- 4.2 Comparison with Other Algorithms -- 5 Conclusion -- References -- Image Compression Based on the Significance Analysis of the Wavelet Transform Coefficients Using the Energy Feature Model -- 1 Introduction -- 2 Wavelet Transform of Images -- 3 Model of Energy Features of the Image -- 4 Image Compression Based on the Energy Feature Model -- 5 Conclusion -- References -- Construction of a Fuzzy Model for Contour Selection -- 1 Introduction -- 2 Building a Fuzzy Inference Model -- 3 Reduction of the Knowledge Base of the Fuzzy Model of Contour Selection -- 4 Determination of the Parameters of the Membership Functions of a Fuzzy Model -- 5 Conclusion -- References -- Identification of Vehicle Trajectory Anomalies on Streaming Video -- 1 Introduction -- 2 Background -- 3 Suggested Approach -- 3.1 Trajectories Extraction -- 3.2 Trajectories Thinning -- 3.3 Trajectories Comparison -- 3.4 Trajectories Clustering -- 3.5 Trajectory Classification -- 4 The Framework for Identification of vehicle's Trajectory Anomalies on Streaming Video -- 5 Evaluation.
Includes bibliographical references and index.

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Online resource; title from PDF title page (SpringerLink, viewed April 6, 2022).

Studies in systems, decision and control ; v. 417. 2198-4190

Print version: 9783030951153

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