Charting the Intelligence Frontiers - Edge AI Systems Nexus (Hardcover)

1. Edge AI Systems Verification and Validation 2. Pioneering the Hybridization of Federated Learning in Human Activity Recognition 3. Edge Intelligence Architecture for Distributed and Federated Learning Systems 4. Challenges and Performance of SLAM Algorithms on Resource-constrained Devices
5. Designing Accelerated Edge AI Systems with Model Based Methodology 6. EDGE AI Hardware Acceleration for Critical Systems: from FPGAs Automatic Hardware Generator to Versatile CGRAs Systems 7. Model Selection and Prompting Strategies in Resource Constrained Environments for LLM-based robotic system 8. Optimising ViT for Edge Deployment: Hybrid Token Reduction for Efficient Semantic Segmentation 9. Recent Trends in Edge AI: Efficient Design, Training and Deployment of Machine Learning Models 10. Scalable Sensor Fusion for Motion Localization in Large RF Sensing Networks 11. The Accountability Strikes Back: Decentralizing the Key Generation in CL-PKC with Traceable Ring Signatures 12. A TinyMLOps Framework for Real-world Applications 13. Transfer and Self-learning in Probabilistic Models 14. A novel hierarchical approach to perform on-device Energy Efficient Fault Classification 15. Discovering and Classifying Digital and Wooden Industries Products’ Defects at the Edge by a Yolo/ResNet-based Approach and Beyond 16. Conscious Agents Interaction Framework for Industrial Automation 17. Neuromorphic IoT Architecture for Efficient Water Management: A Smart Village Case Study 18. Online AI Benchmarking on Remote Board Farms 19. Enhancing Sustainability in Water Resource Management: Optimizing Neural Network Architectures for Accurate Prediction of Water Stress in European Countries 20. Multi-step Object Re-identification on Edge Devices: A Pipeline for Vehicle Re-identification

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