Buch, Englisch, Format (B × H): 155 mm x 235 mm
Proceedings of the 7th Conference on Computing Systems and Applications
Buch, Englisch, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Networks and Systems
ISBN: 978-3-032-43347-3
Verlag: Springer
This book is a comprehensive and up-to-date guide to the recent trends and advances in the rapidly evolving field of computing systems and applications. It gathers selected articles presented at the 7th International Conference on Computing Systems and Applications written by researchers and experts in the field, who present the latest research findings, original ideas, and practical applications that showcase the state-of-the-art developments in computing systems and applications. It is intended for researchers, practitioners, and students who want to learn about the state-of-the-art developments and trends in computer science. The book is also a valuable resource for anyone who wants to explore the potential and impact of computing systems and applications in various domains and disciplines.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Fake News as Anomalies:A Graph Autoencoder Perspective.- Digital Soil Mapping in Data-Scarce Environments Using Neural Networks and Spatial Cross-Validation: Evidence from Northern Algeria.- Ultra-Early Fake News Detection in Social Media Streams via Micro-Burst–Guided Ensemble Deep NLP Models.- Multi-Objective Deep Reinforcement Learning for Emergency Ambulance Dispatching: 2023 Turkey Earthquake Case.- From Trivial to Critical: Leveraging Arbitrary Norms to Enhance Coordination in Generative Agents via In-Context Learning.- Evidential Hypothesis-Gated Fusion for Conflictive Multi-View
Learning.- MOF-FM: A Foundation Model for Metal-Organic Frameworks via Equivariant Graph Learning and Masked Multi-Task Pretraining.- LoRA-ASR: A Parameter-Efficient and Scalable Model for Multilingual ASR.- Pruning Schedules Decide the Outcome: One-Shot vs. Iterative Filter Pruning of CNN Models.- A Comparative Evaluation of Quantization Methods with Architecture Interaction Analysis.- Rethinking Deep Neural Networks Pruning: A Cost Driven Methodology.- A Low-Power FPGA Implementation of Hardware-Accelerated DNN for Autonomous Vehicle Traffic Sign Detection and Color-Based Classification.- Low-Cost Approximate Systolic Array Accelerator Design for FPGA-Based Efficient DNN Processing.- Feature-level Site Leakage Reduction for Cross-Hospital Chest X-ray Transfer via Self-Supervised Learning.- A Deep Learning Framework on Macular OCT for Automated Multi-Attribute Metadata Recovery for Large-Scale Ophthalmic Biobanks.- Adaptive Deep Learning Architectures for Precision Phytopathology: A Benchmarking Study on Olive Diseases in Semi-Arid Agro-Ecological Zones.- DQFormer: Dynamic Query Transformer for Oriented Object Detection in Remote Sensing Imagery.- CaSTMF: Causal Spatio-emporal Multi-Modal Fusion for Land Cover Change Detection.- Distributed Compressive Spectrum Sensing Implementation in Cognitive Radio Networks.- A Game-Theoretic Deep Reinforcement Learning Approach for Edge Caching in the Internet of Vehicles.- Performance Evaluation of 5G, WiFi and LoRa for Smart
Hospitals Applications.- Evaluation of Neural Joint Source-Channel Coding Under Challenging Channel Conditions.- Adaptive Backoff Exponent Selection in IEEE 802.15.4 Networks.- Hybrid Artificial Intelligence and Multi-Agent System Framework for Microgrid Forecasting and Fault Detection.- HGSO-IDS: Bio Inspired Binary Feature Selection for Enhanced IoT Network Intrusion Detection.- Toward Agentic AI for Enabling Targeting in the CTI Lifecycle.- BCAKA: A Novel Balanced Clustering-based Authentication
and Key Agreement Scheme for Securing UAV Swarm Communications.- Constrained Metaheuristic Adversarial Perturbations as a Privacy Shield against IoT Fingerprinting.- Homomorphic encryption for authenticity and interpretability in secure deep learning inference.- Detecting Hallucinations in Medical Question Answering: A Graph-Based Alignment Approach.- Mining Top-k High Utility Sequential Patterns Using Cross Entropy Optimization.- A Digital Twin Framework for Real-Time Traffic Crash Risk Prediction.- Uncertainty-Aware Causal Representation Learning for Reliable and Explainable Early Breast Cancer Diagnosis.
