Buch, Englisch, 510 Seiten, Format (B × H): 155 mm x 235 mm
21st Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2026, Jaén, Spain, November 11–13, 2026, Proceedings
Buch, Englisch, 510 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Lecture Notes in Artificial Intelligence
ISBN: 978-3-032-43169-1
Verlag: Springer
This book constitutes the refereed proceedings of the 21st Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2026, held in Jaén, Spain, during November 11–13, 2026.
The 38 full papers presented in this book were carefully reviewed and selected from 182 submissions. The papers covers such themes as computer vision and robotics; foundational models / LLMs; machine learning; optimization, search and planning; real-world applications; and recommender systems.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Technische Informatik Netzwerk-Hardware
- Sozialwissenschaften Pädagogik Lehrerausbildung, Unterricht & Didaktik E-Learning, Bildungstechnologie
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Geistes- und Sozialwissenschaften
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
Weitere Infos & Material
.- Computer Vision and Robotics .
.- Graph-Based Semantic Segmentation of Agricultural Images Using CNN Features, Vegetation Spectral Indices, and Wavelet Texture Descriptors.
.- Deep Learning-Based Brain Lesion Segmentation Across MRI Registration Templates.
.- Neuromechanical Control of Robotic Limbs using Conformable Fractional Dynamics and Spiking Neural Networks.
.- Deep sMRI features for ordinal classification of Alzheimer’s Disease staging.
.- Foundational Models / LLMs .
.- A Guided Multi-Agent Tutor for Progressive Help in Programming Practice.
.- Is the Extra Compute Worth It? Evaluating Rule Based and Language Model Approaches to Title Generation.
.- Explainable Foundation Models for Epileptic Seizure Detection in Large-Scale Imbalanced EEG Data.
.- Evaluating Cross-Model Consistency of LLM-Generated Sustainability Data for Points of Interest.
.- Benchmarking Chronos-2 as a Foundation Model for Traffic Forecasting.
.- Machine Learning .
.- Harnessing the synergy between the cumulative link model and the SLACE loss in ordinal classification.
.- Statistical Predictors of Optimal Minimum Segment Length for Automated Time-Series Data Volume Reduction.
.- Benchmarking Deep Learning Architectures for Unit Commitment in an Isolated Thermal Power System.
.- Evaluating Artificial Neural Networks with Realistic Memristive Variability.
.- A Study on Self-Supervised Learning Objectives for Intrusion Detection.
.- SpikeLoRA-X: Explainable, Responsible, and Energy-Efficient Spiking Neural Networks for Multi-Horizon Renewable-Energy Forecasting at the Edge.
.- A k-NN-Based Benchmark for Lag Selection in Time Series Forecasting.
.- Lookahead and Dynamic Beam Search Variants of FOCI for Conditional-Dependence Feature Selection.
.- Component analysis of CNN-based architectures for reverse game of life problem.
.- Optimization, Search and Planning .
.- Uncertainty Estimation for Deep Reconstruction in Actuatic Disaster Scenarios with Autonomous Vehicles.
.- Calibrated Uncertainty for Informative Path Planning in Aquatic Environmental Monitoring.
.- A Metaheuristic Approach to Combat Encounter Generation in Dungeons & Dragons.
.- Optimization of Production Line Scheduling: An OGA case study.
.- Reliable Backtesting for Continuous Industrial Optimization via Sequential Simulation:A Gas-Fired Ceramic Kiln Case Study.
.- ADR-EDA: A Reliability-Aware Controller for Dynamic Multiobjective Estimation of Distribution Algorithms.
.- Applying neural combinatorial optimization for the generalized regenerator location problem.
.- A multi-start constructive procedure for test case generation in model transformation testing.
.- Cellular Automata, (µ + ?) Evolutionary Strategies and Morphogenesis: A CBR Approach.
.- The Minimum Vertex Sum Sitting Arrangement on the cycle: Problem Definition and Empirical Analysis.
.- A Hybrid MILP-Multistart Metaheuristic for the Cask Loading Optimization Problem with Minimax Thermal Load: The Case of Asc´o Nuclear Power Plant (2028).
.- Generating Linear Ordering Problem Instances by Controlling Structural Inconsistencies.
.- Real-World Applications.
.- Rule-Based Explainability for Quantum Machine Learning in Thyroid Cancer Prediction.
.- Real-world NLOS validation of novel low-power BLE devices for Indoor Localization.
.- Uncertainty-Aware Neural Runoff Forecasting for Robust Low-Flow Decisions.
.- Real World Implementation of Deep Reinforcement Learning Policies for Environmental Missions with Autonomous Surface Vehicles.
.- On the characterization of glucose data through HAR: An integrated IoMT architecture.
.- Recommender Systems .
.- Improving Music Collaboration Recommendations Using TikTok Social Connections.
.- First, do no harm: Breaking suicidogenic echo chambers in media recommendation.
.- Post-Hoc Dirichlet Fine-Tuning of Variational Autoencoders for Collaborative Filtering: Accuracy Gains and Popularity Costs
