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Distributed Computing for Emerging Smart Networks: 5th International Workshop, DiCES-N 2025, Hammamet, Tunisia, April 26-27, 2025, Revised Selected Papers [Pehme köide]

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  • Formaat: Paperback / softback, 175 pages, kõrgus x laius: 235x155 mm, 30 Illustrations, color; 20 Illustrations, black and white
  • Sari: Communications in Computer and Information Science
  • Ilmumisaeg: 03-Jan-2026
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3032067766
  • ISBN-13: 9783032067760
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Distributed Computing for Emerging Smart Networks: 5th International Workshop, DiCES-N 2025, Hammamet, Tunisia, April 26-27, 2025, Revised Selected PapersSuurem pilt
  • Formaat: Paperback / softback, 175 pages, kõrgus x laius: 235x155 mm, 30 Illustrations, color; 20 Illustrations, black and white
  • Sari: Communications in Computer and Information Science
  • Ilmumisaeg: 03-Jan-2026
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 3032067766
  • ISBN-13: 9783032067760
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783032067760.html
This book constitutes revised selected papers from the 5th International Workshop on Distributed Computing for Emerging Smart Networks, DiCES-N 2025, held in Hammamet, Tunisia, during April 26-27, 2025.



The 7 full papers, 2 short papers and 1 invited paper included in this book were carefully reviewed and selected from 24 submissions. These papers focus on following topical sections: Artificial intelligence for safety and security; Artificial intelligence for e-health.
.- Artificial intelligence for safety and security.


.- Blockchain for Secure and Sustainable Digital Cities:
Innovations, Challenges, and Future Directions.


.- Continual Federated Learning Approach for Distributed Network Intrusion
Detection: A Case Study on Software Defined Networking.


.- On the Optimization of Drone Collision Avoidance using Deep Reinforcement
Learning and Time-to-Collision Estimation.


.- Towards Robust Traffic Prediction: Leveraging GNNs, Data Augmentation, and
Hybrid Models.


.- Towards transitional reconfiguration of WSNs distributed algorithms.


.- Artificial intelligence for e-health.


.- Advancing Smart Healthcare with an Enhanced Multi-Modal for Med-VQA.


.- Improving Clinical Diagnosis: An Enhanced 3D U-Net Architecture with SE
Blocks for Brain Tumor Segmentation.


.- AI-Powered Early Detection of Ophthalmic Diseases through Eye Aspect Ratio
Analysis in Smartphone Videos: Dry Eye and Refractive Errors Diseases
Study-Case.


.- Artificial Intelligence in Sleep Apnea Detection: A Review.


.- Advancements in Image Segmentation Techniques for Uterine Diseases:A
Comprehensive Review.