Proceedings of the 15th International Conference on Computer Engineering and Networks : Volume I (Lecture Notes in Electrical Engineering)

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Proceedings of the 15th International Conference on Computer Engineering and Networks : Volume I (Lecture Notes in Electrical Engineering)

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  • 製本 Hardcover:ハードカバー版
  • 言語 ENG
  • 商品コード 9789819533190

Full Description

This book collects papers accepted by CENet2025 - the 15th International Conference on Computer Engineering and Networks, held in Hefei, China, 17-19 October 2025. The topics covered include Internet of Things and Smart Systems, Artificial Intelligence and Applications, Detection, Analysis and Application of Communication Systems, Cloud Computing and Security, and Medical Engineering and Information Systems. Each section of this book can serve as an excellent reference for industry practitioners, university faculty, research fellows, undergraduate and graduate students who wish to build a knowledge base of the latest advances and state-of-the-art practices in the topics covered. Using this knowledge, they will be able to design, implement and manage systems that are both complex and trustworthy. We would like to thank the authors for their hard work and dedication, and the reviewers for their efforts in ensuring that only the highest quality papers were selected. Without their contributions, the proceedings would not have been possible.

Contents

Chapter 1:Fault Diagnosis System Construction for an Electromechanical System Based on Knowledge Map.- Chapter 2: Collaborative Task Offloading and Computing Resource Allocation Based on DDPG Algorithm for UAV Networks.- Chapter 3: Overview of Hybrid Semantic-Bit Communication Systems: Architecture, Technology and Challenges.- Chapter 4: Research on key technology of Trojan Horse traffic detection based on semi-supervised learning.- Chapter 5: Semantic Communication and Control Co-Optimization: A Survey of Models, Technologies, and Challenges.- Chapter 6: AC_UNet: An Urban Waterlogging Segmentation Method Based on Multi-scale Feature Enhancement.- Chapter 7: Multi-modal Object Detection with Improved Faster R-CNN.- Chapter 8: An Uncertainty-guided semantic transformation adversary learning algorithm for Dynamic operation and Inspection Services.- Chapter 9: Generative Adversarial and Semi-Supervised Optimization of Dynamic Occlusion Scenes in Mulberry Leaves Research.- Chapter 10: SNN-ANN Hybrid Architectures in Wireless Edge Scenarios: Principles, Challenges, and Prospects.

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