Hybrid Artificial Intelligent Systems : 20th International Conference, HAIS 2025, Salamanca, Spain, October 16-17, 2025, Proceedings, Part I (Lecture Notes in Computer Science)

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Hybrid Artificial Intelligent Systems : 20th International Conference, HAIS 2025, Salamanca, Spain, October 16-17, 2025, Proceedings, Part I (Lecture Notes in Computer Science)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 309 p.
  • 言語 ENG
  • 商品コード 9783032084644

Full Description

This book constitutes the proceedings of the 20th International Conference on Hybrid Artificial Intelligence Systems, HAIS 2025, held in Salamanca, Spain, during October 16-17, 2025.

The 53 full papers included in this book were carefully reviewed and selected from 120 submissions. They focus on the following topical sections:

Part I: Agricultural and Environmental Monitoring; Biomedical Applications; Cybersecurity and Network Protection; Data Mining and Decision Support Systems.

Part II: Deep Learning and Representation Learning; HAIS Energy Applications; Evolutionary Computation and Optimization; Reinforcement Learning and AI Planning; Smart Mobility and Transportation Optimization; Time Series and Forecasting Methods.

Contents

.- Agricultural and Environmental Monitoring.

.- Comparative Analysis of Cattle Behavior Across Intensive Dairy Farms through Dimensional Reduction Techniques.

.- Environmental Sound Recognition for Human-Robot Interaction in Social Robots.

.- A new Transformer-based hybrid model to forecast olive fruit fly using multimodal data.

.- Infrared Driver Monitoring Systems - A Review, New Opportunities and Trends.

.- Ambient Intelligence Integration in Vocational Education: Evaluating Smart Learning Environments for Digital Skills Development.

.- Zero-shot and Few-shot Learning with Vision-Language Models for post-disaster Structural Damage Assessment.

.- Biomedical Applications.

.- Analyzing the Impact of Data Augmentation on Tumor Detection and Classification in Mammograms.

.- An Enhanced Hybrid Machine Learning Model for Plant Disease Detection and Classification.

.- Interpretable ML for Stress Detection from Vital Signs Using SHAP.

.- Learning from Normal Brain Activity for Automatic Detection of Photoparoxysmal Responses as Electroencephalographic Anomalies.

.- Subsymbolic and Symbolic Pipeline for an Explainable EEG Authentication System.

.- Cybersecurity and Network Protection.

.- Analyzing DoS Attacks on CoAP Networks Using Low-Dimensional Latent Representations.

.- An Approach to Anomaly Detection with Dynamic Threshold Definition for Real-World Environments.

.- Loss Functions for Time Series Forecasting in Network Security Situation Awareness.

.- A Hybrid Feature Selection Approach Using Filter-Wrapped Evaluation (FWE) for Attack Detection in SDN.

.- RAG embeddings storage optimization through quantization and dimensionality reduction.

.- Exploratory Visualization of IoT Attacks on the NF-CSE-CIC-IDS2018 dataset.

.- Data Mining and Decision Support Systems.

.- A Microservice System Architecture for Receiving ETL System.

.- A Novel General Hybrid System for Data Feature Selection.

.- Profiling Public Instagram Accounts with a Multimodal Vector for Hate Exposure Analysis.

.- Symbolic Regressor: a interpretability tool for Non-Intrusive Load Monitoring.

.- IoT Device Fingerprinting: Optimized with Data Diversity and Feature Selection for Computational Efficiency.

.- Improvement of Multi-Label Self-Adjusting Memory kNN Classifier for Sparse and Class-Imbalanced Data Streams.

.- HYBPARSIMONY-IDT: Hybrid Parsimonious Search for Interpretable Decision Trees.

.- Analysis of Kernel Thinning for Scalable Support Vector Machines.

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