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Advances in Artificial Intelligence 20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, A Coruña, Spain, June 19–21, 2024, Proceedings /

This book constitutes the refereed proceedings of the 20th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2024, held in A Coruña, Spain, during June 19–21, 2024. The 27 full papers presented in this book were carefully reviewed and selected from 38 submissions. CAEPIA is a...

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Bibliografiske detaljer
Institution som forfatter: SpringerLink (Online service)
Andre forfattere: Alonso-Betanzos, Amparo (Editor), Guijarro-Berdiñas, Bertha (Editor), Bolón-Canedo, Verónica (Editor), Hernández-Pereira, Elena (Editor), Fontenla-Romero, Oscar (Editor), Camacho, David (Editor), Rabuñal, Juan Ramón (Editor), Ojeda-Aciego, Manuel (Editor), Medina, Jesús (Editor), Riquelme, José C. (Editor), Troncoso, Alicia (Editor)
Format: Electronisk eBog
Sprog:engelsk
Udgivet: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Udgivelse:1st ed. 2024.
Serier:Lecture Notes in Artificial Intelligence, 14640
Fag:
Artificial intelligence.
Computer networks .
Social sciences > Data processing.
Education > Data processing.
Computer vision.
Application software.
Artificial Intelligence.
Computer Communication Networks.
Computer Application in Social and Behavioral Sciences.
Computers and Education.
Computer Vision.
Computer and Information Systems Applications.
Online adgang:https://doi.org/10.1007/978-3-031-62799-6
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Indholdsfortegnelse:
  • -- Taking Advantage of Depth Information for Semantic Segmentation in Field-Measured Vineyards.
  • Advancing Computational Frontiers: Spiking Neural Networks in High-Energy Efficiency Computing Across Diverse Domains.
  • Deep Variational Auto-Encoder for Model-based Water Quality Patrolling with Intelligent Surface Vehicles.
  • An Architecture Towards Building a Reliable Suicide Information Chatbot.
  • Age estimation using soft labelling ordinal classification approaches.
  • O-Hydra: a hybrid convolutional and dictionary-based approach to Time Series Ordinal Classification.
  • Predicting Parkinson’s Disease Progression: Analyzing Prodromal Stages through Machine Learning.
  • Ground-Level Ozone Forecasting using Explainable Machine Learning.
  • Multi-Objective Lagged Feature Selection based on Dependence Coefficient for Time-Series Forecasting.
  • FuSDG: A proposal for a fuzzy assessment of Sustainable Development goals achievement.
  • A surrogate assisted approach for fitness computation in robust optimization over time.
  • A Path Relinking-based approach for the Bi-Objective Double Floor Corridor Allocation Problem.
  • An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines.
  • Preserving the Essential Features in CNNs: Pruning and Analysis.
  • Iterated Local Search for the Facility Location problem with Limited Choice rule.
  • Driven PCTBagging: Seeking greater discriminating capacity for the same level of interpretability.
  • Semi-supervised learning methods for Semantic Segmentation of Polyps.
  • Community-Based Topic Modeling with Contextual Outlier Handling.
  • Toward Explaining Competitive Success in League of Legends: A Machine Learning Analysis.
  • Reconstruction-based Anomaly Detection in Wind Turbine Operation Time Series using Generative Models.
  • Multi-class and Multi-label Classification of an Assembly Task in Manufacturing.
  • Image Processing and Deep Learning Methods for the Semantic Segmentation of Blastocyst Structures.
  • Multivariate-Autoencoder flow-analogue method for heat waves reconstruction.
  • HEX-GNN: Hierarchical EXpanders for Node Classification.
  • The notion of bond in the multi-adjoint concept lattice framework.
  • Exploring the use of LLMs for teaching AI and Robotics concepts at a Master's Degree.
  • Exploring the Capabilities and Limitations of Neural Methods in the Maximum Cut.

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