Wireless Artificial Intelligent Computing Systems and Applications : 18th International Conference, WASA 2024, Qindao, China, June 21-23, 2024, Proceedings, Part I (Lecture Notes in Computer Science) (2024)

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Wireless Artificial Intelligent Computing Systems and Applications : 18th International Conference, WASA 2024, Qindao, China, June 21-23, 2024, Proceedings, Part I (Lecture Notes in Computer Science) (2024)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 520 p.
  • 言語 ENG
  • 商品コード 9783031714634

Full Description

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.

Contents

.- 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.

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