Wireless Artificial Intelligent Computing Systems and Applications
Springer International Publishing (Verlag)
978-3-031-71463-4 (ISBN)
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The three-volume proceedings set LNCS 14997-14999 constitutes the refereed proceedings of the 18th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2024, held in Qindao, China, during June 21-23, 2024.
The 98 full papers and 10 short papers included in these proceedings were carefully reviewed and selected from 301 submissions. They focus on cutting-edge ideas, research findings, and innovative solutions in the dynamic intersection of wireless technologies and artificial intelligence (AI) computing systems.
.- FEKNN: A Wi-Fi Indoor Localization Method Based on Feature Enhancement and KNN.
.- Smartphone Indoor Fusion Localization with Trust Region-Based Magnetic Matching.
.- Multi-agent Deep Reinforcement Learning-based UAV-enable NOMA Communication Networks Optimization.
.- BufferConcede: Conceding Buffer for RoCE Traffic in TCP/RoCE Mix-Flows.
.- An Effective Cooperative Jamming-based Secure Transmission Scheme for a Mobile Scenario.
.- ID-Gait: Fine-grained Human Gait State Recognition using Wi-Fi Signal.
.- Anti-Packet-Loss Encrypted Traffic Classification via Masked Autoencoder.
.- Graph Transformer Hawkes Processes for Causal Structure Learning in Telecom Networks.
.- Design of Maritime End-to-End Autoencoder Communication System Based on Compressed Channel Feedback.
.- ZigRa: Physical-layer Cross-Technology Communication from ZigBee to LoRa.
.- Wireless Portable Dry Electrode Multi-channel sEMG Acquisition System.
.- A Double Layer Consensus Optimization Mechanism in DAG-based Blockchain for Carbon Trading.
.- Probabilistic Offloading Algorithm for Opportunistic Networks Integrating Node Influence Prediction.
.- Secret Sharing Based Key Agreement Protocol for Body Area Networks.
.- Active Detection Based NTP Device Attribute Detection.
.- Cyber Sentinel: Fortifying Voice Assistant Security with Biometric Template Integration in Neural Networks.
.- Traceable Health Data Sharing Based on Blockchain.
.- KD-Eye: Lightweight Pupil Segmentation for Eye Tracking on VR Headsets via Knowledge Distillation.
.- Meta-RFF: Few-Shot Open-Set Incremental Learning for RF Fingerprint Recognition via Multi-phase Meta Task Adaptation.
.- Left Ventricular Hypertrophy Detection Algorithm Using Feature Selection and CNN-LSTM.
.- Application with Digital Currencies Trading Using Machine Learning.
.- Mobile Crowdsourcing Task Assignment Algorithm Based on ConvNeXt and GRU.
.- Inferring the Number of Clusters for Radar Emitters via Threshold Segmentation and Information Fusion.
.- Enhancing Student Classroom Behavior Detection Using Improved SlowFast.
.- LV-auth: Lip Motion Fusion for Voiceprint Authentication.
.- Generative Model-Based Edge-Assisted Object Detection in Bandwidth-Constrained Network.
.- Enhancing Generalized Zero-shot Learning with Dynamic Selective Knowledge Distillation.
.- BehaMiner: System Behavior Mining for Audit Log based on Graph Learning.
.- REHG: A Recommender Engine Based on Heterogeneous Graph.
.- Step-by-Step and Tailored Teaching: Dynamic Knowledge Distillation.
.- TBA-GNN: A Traffic Behavior Analysis Model with Graph Neural Networks for Malicious Traffic Detection.
.- Enhancing Adversarial Robustness in Automatic Modulation Recognition with Dynamical Systems-Inspired Deep Learning Frameworks.
.- E-SAGE: Explainability-based Defense Against Backdoor Attacks on Graph Neural Networks.
.- Sophon IDS: Mitigating the Effectiveness of GAN-based Adversarial Attacks via Tailored Misinformation.
.- An Early Warning Method for Fracturing Accidents Using Joint CNN and LSTM Modeling.
.- Defense Strategy in Federated Learning: Unveiling Stealthy Threats and the Similarity Filter Solution.
.- FedScale: A Federated Unlearning Method Mimicking Human Forgetting Processes.
.- The Client-level GAN-based Data Reconstruction Attack and Defense in Clustered Federated Learning.
.- Byzantine-Robust Federated Learning Based on Blockchain.
.- FedDue: Optimizing Personalized Federated Learning through Dynamic Update Classifier.
.- FedDCT: A Dynamic Cross-Tier Federated Learning Framework in Wireless Networks.
| Erscheint lt. Verlag | 16.12.2024 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science |
| Zusatzinfo | XX, 498 p. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Technik ► Elektrotechnik / Energietechnik | |
| Technik ► Nachrichtentechnik | |
| Schlagworte | Artificial Intelligence • Computing Methodologies • distributed computing methodologies • machine learning • network algorithms • Network Architectures • network performance evaluation • Network Protocols • Networks • Network Security • network services • Security and Privacy • Systems Security |
| ISBN-10 | 3-031-71463-6 / 3031714636 |
| ISBN-13 | 978-3-031-71463-4 / 9783031714634 |
| Zustand | Neuware |
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