Advanced Intelligent Computing Technology and Applications

.- Intelligent Computing in Communication Networks

.- UAV cluster dynamic deployment in edge data acquisition system.
.- Multi-cluster Layer-sharing Container Scheduling in Cloud-Edge Collaboration.
.- FairMS: Fair DNN Model Selection Algorithm for Collaborative Edge Intelligence.
.- Delay-Energy Tradeoff for Intelligent Online Partial Offloading in Mobile Edge Computing.
.- A Consortium Blockchain Framework for Low-Storage Coal Mine Dispatch Speech System.
.- Federated Dynamic Aggregation Learning Based on Parameter Decomposition to Combat Noisy Data.
.- QoE Oriented Efficient MEC-Assisted Rendering Scheme for Virtual Reality.
.- IAE-LoRa: Interference-Aware and Energy-Efficient LoRa Optimization using Reinforcement Learning.
.- SecureNT: Smart Topology Obfuscation for Privacy-Aware Network Monitoring.
.- Data Annotation Crowdsourcing Matching Optimization Method in Blockchain Environment: Based on Deep Reinforcement Learning.
.- Joint Resource Allocation for Downlink NOMA-Assisted CR-SWIPT System.
.- A Cross-Layer and Multi-Center Authentication Fusion Framework for Mobile Industrial Internet of Things.
.- MENTOR: Malicious Network Traffic Detection Through Optimized LLM based Recognition.
.- EDGaE: Efficient Distributed Graph Neural Network Training System at the Edge.
.- Dynamic Service Migration and Resource Allocation for UAV-Assisted Vehicular Edge Computing.
.- Intelligent Routing Decision Making Based on GGKM: Combining GCN and Deep Reinforcement Learning.
.- INT-LLM: Adaptive Path Planner for In-band Network Telemetry via Large Language Models.
.- PIKA: A Rate Control Mechanism for Real-Time Video Streaming Assisted by 5G Link Quality.
.- SatDetector: Critical Nodes Detection for LEO Satellite Networks Based on Evolutionary Algorithm.
.- Tongs: A Multi-Objective Scheduling Framework for Network Flow.
.- Bimodal Data-Driven Optimization of Human Action Recognition: Combining CSI and Video Intelligence Analysis.
.- Automated Cloud-Native Dynamic Network Policy Generation Based on Microservices Topology.

.- Intelligent Computing in Finance Banking

.- Deep Reinforcement Learning-based Portfolio Optimization with Black Litterman Model under Elliptical Distributions.
.- FAEF: Frequency-Adaptive Economics Forecasting That Works.
.- Semantic Information Tells the Truth: A Novel Approach to Numerical Veracity for Large Language Models in Financial Market Analytics.
.- Asset-Centric Factor-Opinion Pair Extraction from Market Analysis Reports.
.- Large Language Model-guided DeepFutures for Accurate Domestic Futures Trading.
.- LightFSA: A Lightweight Financial Sentiment Analysis Model.
.- Hidden Market Patterns: A Spatio-temporal Graph Auto-Encoder for Stock Price Forecasting and Portfolio Optimization Strategy.
.- Deep Multi-View Factor Entropy Pooling: A Novel Framework for Adaptive Portfolio Optimization.
.- Overnight Stock Movement Prediction Based on Dynamic Graph Neural Networks.
.- Fraud Detection Based on Dynamic Graph Neural Networks.

.- Virtual Reality and Human-Computer Interaction

.- Spatial-Aware Anchor Growth for 3D Gaussian Field Reconstruction.
.- EMFIN: A Multimodal Fusion Algorithm and Intelligent Navigation System for Intelligent Chemistry Experiments.
.- AMC-Net: Adaptive Multi-Channel Sampling and Deep Reconstruction for Block-Based Image Compressive Sensing.
.- ULTRA-Net: An Efficient and Interpretable Deep Network for Low-Dose CT Images Denoising.
.- GESTURE-MINE: A Gesture Interaction-based VR enhancement for Mine Safety Inspection Training.
.- Attention-Modulated Transformer for In-Air Handwriting Recognition.
.- ARR-Net: An Adaptive Redundancy Reduction Network for Compressed Sensing.
.- HD-Tex: Leveraging Structural Priors for High-Fidelity Texture Synthesis.
.- AR-VitalSense: Enabling Real-Time Vital Sign Monitoring in Dynamic Environments.
.- JoyLive: Efficient audio-driven portrait animation by 3D implict keypoints.
.- MLAD: A Two-Stage Fully Automated Multi-Perspective Tabular Data Anomaly Detection Framework.

• Erscheinungsdatum: 16.07.2025
• Autor/Autorin: De-Shuang Huang
• Reihe: Lecture Notes in Computer Science
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 77 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 525 Seiten
• ISBN: 9789819699148
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.