Advances in Artificial Intelligence : 20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, a Coruña, Spain, June 19-21, 2024, Proceedings

• Autore: Alonso-Betanzos Amparo
• Pubblicazione: Cham : , : Springer International Publishing AG, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (293 pages)
• Altri autori: Guijarro-BerdiñasBertha Bolón-CanedoVerónica Hernández-PereiraElena Fontenla-RomeroOscar CamachoDavid RabuñalJuan Ramón Ojeda-AciegoManuel MedinaJesús RiquelmeJosé C
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Taking Advantage of Depth Information for Semantic Segmentation in Field-Measured Vineyards -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Computational Methods -- 3 Results and Discussion -- 4 Conclusions and Further Work -- References -- Advancing Computational Frontiers: Spiking Neural Networks in High-Energy Efficiency Computing Across Diverse Domains -- 1 Introduction -- 2 Related Work -- 3 Comprehensive Exploration of SNNs -- 3.1 Encoding Techniques -- 3.2 Neuron Models: SNNs Architectures for Energy Efficiency -- 3.3 Training Paradigms and Learning Methods in SNNs -- 4 Discussion in SNN Research for Energy Efficiency -- 5 Conclusion and Future Directions in SNNs Research -- References -- Deep Variational Auto-Encoder for Model-Based Water Quality Patrolling with Intelligent Surface Vehicles -- 1 Introduction -- 2 Previous Works -- 3 Statement of the Problem -- 4 Methodology -- 4.1 VAE-UNet Architecture -- 4.2 Multiagent Path Planning -- 5 Results -- 5.1 UNet-VAE Training Results -- 5.2 Patrolling Results -- 6 Conclusions and Future Work -- References -- An Architecture Towards Building a Reliable Suicide Information Chatbot -- 1 Introduction -- 2 Architecture of the Chatbot -- 2.1 Text Classification Filter for Not Suicidal Content -- 2.2 Text Classification Filter for Not Safe Information About Suicide -- 2.3 Retrieval Augmented Generation Module -- 3 Evaluation -- 4 Conclusions and Further Work -- References -- Age Estimation Using Soft Labelling Ordinal Classification Approaches -- 1 Introduction -- 2 Soft Labelling Methodology -- 3 Age Estimation Problems -- 4 Experimental Settings -- 4.1 Model Selection -- 4.2 Compared Methodologies -- 5 Results -- 6 Conclusions -- References. ; O-Hydra: A Hybrid Convolutional and Dictionary-Based Approach to Time Series Ordinal Classification -- 1 Introduction -- 2 Methodology -- 2.1 Preliminary Definitions -- 2.2 Dictionary-Based Methods -- 2.3 Convolution-Based Methods -- 2.4 O-Hydra Approach -- 3 Experimental Setup -- 4 Results -- 5 Conclusions -- References -- Predicting Parkinson's Disease Progression: Analyzing Prodromal Stages Through Machine Learning -- 1 Introduction -- 2 Data -- 2.1 Database Description -- 2.2 Demographic and Clinical Data -- 2.3 Structural MRI Data -- 2.4 Pre-processing -- 3 Methodology -- 3.1 Feature Selection -- 3.2 Classification Algorithms -- 3.3 Classification Performance Evaluation -- 3.4 Explanation -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- Ground-Level Ozone Forecasting Using Explainable Machine Learning -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Machine Learning -- 3.2 Hyperparameter Optimization -- 3.3 XAI -- 4 Results -- 4.1 Input Data -- 4.2 Evaluation Metrics -- 4.3 ML Optimization -- 4.4 XAI -- 5 Conclusions and Future Works -- References -- Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting -- 1 Introduction -- 2 Related Works -- 3 Description of the Proposed MOLS Algorithm -- 4 Methodology and Experimentation -- 4.1 Model -- 4.2 Main Phases -- 5 Results and Discussion -- 5.1 Datasets -- 5.2 Result and Analysis -- 6 Conclusions and Future Works -- References -- FuSDG: A Proposal for a Fuzzy Assessment of Sustainable Development Goals Achievement -- 1 Introduction -- 2 Definition of a Fuzzy SDG Index (FuSDG) -- 3 Case Study -- 4 On the Impact of Prioritization of the SDG -- 5 Discussion and Conclusions -- References -- A Surrogate Assisted Approach for Fitness Computation in Robust Optimization over Time -- 1 Introduction -- 2 Proposed Approach. ; 3 Computational Experiments -- 3.1 Computational Complexity -- 3.2 Experiment Results -- 4 Conclusion and Future Works -- References -- A Path Relinking-Based Approach for the Bi-Objective Double Floor Corridor Allocation Problem -- 1 Introduction -- 2 Problem Description -- 3 Optimization Proposal -- 3.1 Bi-Objective PR -- 3.2 Path Relinking -- 3.3 Algorithmic Description -- 4 Results -- 5 Conclusions and Future Work -- References -- An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines -- 1 Introduction -- 2 Related Works -- 3 Fundamentals -- 3.1 Quantum Fundamentals -- 3.2 Support Vector Machines -- 4 Methodology -- 5 Results -- 5.1 Quality Parameters -- 5.2 Dataset Description -- 5.3 Discussion -- 6 Conclusions -- References -- Preserving the Essential Features in CNNs: Pruning and Analysis -- 1 Introduction -- 2 Filter Pruning Strategy -- 2.1 Layer Essential Features -- 2.2 Pruning Method -- 3 Experiments and Results -- 3.1 Experimental Setting -- 3.2 Pruning Setting -- 3.3 Comparing Different Filter Selection Criteria -- 3.4 Results -- 4 Discussion on the Importance of Retaining the Essential Features -- 5 Conclusion -- References -- Iterated Local Search for the Facility Location Problem with Limited Choice Rule -- 1 Introduction -- 2 Formal Description of the Problem -- 3 Iterated Local Search -- 4 Computational Experiments -- 5 Conclusions and Future Work -- References -- Driven PCTBagging: Seeking Greater Discriminating Capacity for the Same Level of Interpretability -- 1 Introduction -- 2 Related Work on PCTBagging -- 3 Driven PCTBagging -- 4 Experimental Methodology -- 5 Experimental Results -- 6 Conclusions and Further Work -- References -- Semi-supervised Learning Methods for Semantic Segmentation of Polyps -- 1 Introduction -- 2 Materials and Methods -- 2.1 Dataset. ; 2.2 Base Training Procedure -- 2.3 Distillation Methods -- 3 Results -- 4 Conclusions and Further Work -- References -- Community-Based Topic Modeling with Contextual Outlier Handling -- 1 Introduction -- 2 Related Work -- 3 Our Proposal -- 4 Experimental Study -- 4.1 The Datasets -- 4.2 Experimental Setup -- 5 Results -- 5.1 NCM4 and NCM8 Datasets -- 5.2 News and Tweets Datasets -- 6 Conclusions -- References -- Toward Explaining Competitive Success in League of Legends: A Machine Learning Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Models -- 3.3 Experimental Settings -- 3.4 Evaluation Metrics -- 3.5 Hyperparameter Optimization -- 4 Results -- 4.1 Best Models -- 4.2 Global Analysis -- 4.3 Role Analysis -- 4.4 Local Analysis -- 5 Conclusions and Future Works -- References -- Reconstruction-Based Anomaly Detection in Wind Turbine Operation Time Series Using Generative Models -- 1 Introduction -- 2 Background -- 2.1 Anomaly Detection in Time Series -- 2.2 Failure Detection in Wind Turbines -- 3 Methodology -- 4 Experimental Setup and Results -- 4.1 Dataset -- 4.2 Experimental Evaluation -- 4.3 Results and Discussion -- 5 Conclusions and Future Work -- References -- Multi-class and Multi-label Classification of an Assembly Task in Manufacturing -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Conclusions and Further Work -- References -- Image Processing and Deep Learning Methods for the Semantic Segmentation of Blastocyst Structures -- 1 Introduction -- 2 Related Work -- 3 Materials and Methods -- 3.1 Data Source -- 3.2 Proposal Description -- 3.3 Experimentation Setup -- 4 Results and Discussion -- 5 Conclusions and Further Work -- References -- Multivariate-Autoencoder Flow-Analogue Method for Heat Waves Reconstruction -- 1 Introduction -- 2 Methodology -- 2.1 Data. ; 2.2 The Multivariate Analogue Method -- 2.3 The MvAE-AM Approach -- 3 Experiments and Results -- 4 Conclusions -- References -- HEX-GNN: Hierarchical EXpanders for Node Classification -- 1 Introduction -- 2 Related Works -- 3 Preliminaries -- 4 Method -- 5 Experimental Settings -- 5.1 Datasets -- 5.2 Settings -- 6 Results and Analysis -- 7 Conclusion and Future Work -- References -- The Notion of Bond in the Multi-adjoint Concept Lattice Framework -- 1 Introduction -- 2 Preliminaries -- 3 Bonds on a Multi-adjoint Framework -- 4 Conclusions and Future Work -- References -- Exploring the Use of LLMs for Teaching AI and Robotics Concepts at a Master's Degree -- 1 Introduction -- 1.1 Contribution -- 2 State of the Art -- 3 Materials and Methods -- 3.1 Courses -- 3.2 LLMs Impact -- 4 Practical Case -- 4.1 Project Description -- 4.2 llama.cpp -- 4.3 llama_ros -- 4.4 Mini Pupper -- 4.5 ChatBot Application -- 5 Discussion and Conclusions -- References -- Exploring the Capabilities and Limitations of Neural Methods in the Maximum Cut -- 1 Introduction -- 2 Background and Limitations -- 3 Case Study: NCO for the Maximum Cut -- 3.1 Maximum Cut Problem -- 3.2 NCO Model -- 4 Experiments -- 4.1 RQ1-A. Generalization to Different Graph Connectivity Levels -- 4.2 RQ1-B. Generalization to Different Graph Sizes -- 4.3 RQ2. Confidence Level of NCO Models -- 4.4 RQ3. Strategies to Minimize Training Costs -- 4.5 RQ4. NC Vs NI -- 5 Conclusion -- References -- Author Index.
• Titolo autorizzato: Advances in Artificial Intelligence
• ISBN: 9783031627996; 9783031627989
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910865239103321
• Lo trovi qui: Univ. Federico II
• Serie: Lecture Notes in Computer Science Series