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Mobile Radio Communications and 5G Networks

Proceedings of Sixth MRCN 2025
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Inhaltsangabe

Zero Day Malware Detection Using Hybrid Deep Learning Model GRU and LSTM.- A Comprehensive Hybrid Ensemble Framework for Software Fault Prediction.- Deep Search:An Approach Towards Tamil Character Recognition In Ancient Inscriptions.- Lunar Surface Scattering Mechanisms Revealed Through Polarization Channel Outputs and Signature Analysis from Chandrayaan-2 SAR.- A Hybrid EfficientNetB0 and Metadata Fusion Model for  Binary Skin Cancer Detection.- Machine Learning at the Crossroads of Industry and Ecology: A Case Study of Haridwar’s SIDCUL Using GEE.- Silicon Wafer Defect Detection Using CNN and VGG16-Based Transfer Learning.- Green Intelligence: Energy-Efficient Power Management in Software-Defined Wireless Infrastructures.- Heterogeneous Harmony: Optimizing Inter-networking in Multi-Tier Wireless Environments.- AI-Enabled High-Gain Micro-Strip Antenna for Defense System.- Comparative performance analysis of IFP-Augmented, Cluster-based, and Multipath routing techniques in VANET Environment.- A Robust Ensemble Method for Liver Disorder Detection.- Wearable Multi-Band Microstrip Patch Antennas for Wireless communications and IoT Applications.- Temporal Dynamics of Galvanic Skin Response for Cognitive Stress Detection.- Automated 3D Modeling from 2D Floor Plans via YOLOv8-Driven Structural Feature Extraction.- Impact of Activation Functions on Deep Learning Models Based on Meta-Heuristics Algorithms for the Diagnosis of Breast Cancer.- Mining E-Commerce Data for Consumer Trend Pre-diction with ML.- Unsupervised Classification of Banana Ripening Phases using Principal Component Analysis and K-Means Clus-tering.- Voice2Sign: Automated Translation of Indian Sign Language Gestures from Speech Using Machine Learning.- Short-Term Solar Irradiance Forecasting for Energy-Efficient Infrastructure: A Deep Learning Case Study of Delhi.- Cybersecurity Challenges in 5G Networks: A Risk Management Framework for Threat Mitigation.- Heart Diseases Prediction Using Ensemble Model.- Development of a Power-Efficient Built-In Self-Test (BIST) Framework for Memory Systems.- Seismic Damage Prediction in Structures Using Neural Networks: A Deep Learning Approach for Earthquake-Resilient Design.- Assessment of Current Energy Management Techniques and Future Trends in Energy Harvesting Wireless Sensor Networks.- Multiuser Detection for NOMA-PD-SCMA System in Nakagami-m Fading Channel Using DNN Algorithm.- A Hybrid Heuristic Approach in High Workload Scheduling for Cloud Computing Using a combination of FCFS, HEFT and RASA.- Defakeit: AI-powered Deepfake Media Detection Model and Anti-Spoofing System.- Deep Learning Based Bone Mineral density Assessment for Opportunistic Osteoporosis.- 5G Network Coverage Analysis and Forecasting.- Algorithm-Driven Resource Allocation Framework For 5G Network Slicing.- Real-Time Positioning and Tracking System for 5G Networks.- A Novel 1-bit Fast and Low Power 17-T Full Adder Circuit at 45 nm Technology Node.- An Adaptive Hybrid Model for Accurate and Scalable Community Detection in Dynamic Social Networks.- Low-Power 4:2 Approximate Compressor Design with FinFET.- Smart Parking and Reservations System for Aerial Vehicles.- Landslide Prediction and Warning Systems using Wireless Sensor Networks.- Unveiling the Key Predictors of Adoption Intention towards Gen-AI chatbots of Higher Education Students.- Strategic Synergy: Integrating Harris Hawk Particle Swarm Optimization (HHPSO) and Deep LSTM for Robust Cancer Categorization with Microarray Data.- Adaptive AI for Pattern Recognition: Novel Techniques Using Unstructured Data for Computer Vision Application.

Produktdetails
  • Erscheinungsdatum: 10.09.2026
  • Autor/Autorin: Nikhil Kumar Marriwala
  • Format: E-Book
  • Dateiformat: PDF
  • Kopierschutz: Wasserzeichen
  • Dateigröße: 80.2 MB
  • Verlag: SPRINGER
  • Sprache: Englisch
  • Umfang: 538 Seiten
  • ISBN: 9783032310972
  • Lieferung: Sofort per Download
  • Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
  • Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.
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