Intelligent Data Engineering and Automated Learning – IDEAL 2024 : 25th International Conference, Valencia, Spain, November 20–22, 2024, Proceedings, Part I / / edited by Vicente Julian, David Camacho, Hujun Yin, Juan M. Alberola, Vitor Beires Nogueira, Paulo Novais, Antonio Tallón-Ballesteros

• Record Nr.: UNISA996630864103316
• Autore: Julian Vicente
• Pubbl/distr/stampa: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025
• ISBN: 9783031777318
• Edizione: [1st ed. 2025.]
• Descrizione fisica: 1 online resource (541 pages)
• Collana: Lecture Notes in Computer Science, , 1611-3349 ; ; 15346
• Altri autori (Persone): CamachoDavid; YinHujun; AlberolaJuan M; NogueiraVitor Beires; NovaisPaulo; Tallón-BallesterosAntonio
• Disciplina: 006.312
• Soggetti: Data mining; Machine learning; Software engineering; Education - Data processing; Computer vision; Data Mining and Knowledge Discovery; Machine Learning; Software Engineering; Computers and Education; Computer Vision
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: -- Quantitative Estimation of Reputation Risk. -- Dissecting Data Practices in Android Apps: A Comparative Study of Data Collection and Sharing Behaviors. -- Model-Based Meta-Reinforcement Learning for Hyperparameter Optimization. -- Towards Sustainable Precision: Machine Learning for Laser Micromachining Optimization. -- ; Association Rules Mining with Auto-Encoders. -- Using Contrastive Learning to Map Stylistic Similarities in Narrative Writers. -- Automatic classification of signal and noise in functional magnetic resonance imaging scans using convolutional neural networks. -- How Resilient are Language Models to Text Perturbations?. -- Emotional Sequential Influence Modeling on False Information. -- CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care Data Interoperability. -- Padel two-dimensional tracking extraction from monocular video recordings. -- Drowsiness Detection Using Vital Sign Sensors and Deep Learning on Smartwatches. -- Benchmarking out of the box Open-Source LLMs for Malware Detection based on API Calls sequences. -- Multimodal Visio-lingual Content Analysis to Detect Fake Content on Reddit. -- MetaLIRS: Meta-learning for Imputation and Regression Selection. -- Pipeline for Semantic Segmentation of Large Railway Point Clouds. -- Preliminary Investigation on Machine Learning and Deep Learning Models for Change of Direction Classification in Running. -- Efficient Radar Scheduling Using Genetic Algorithms and Stochastic Heuristic Initialization. -- Towards a Communication Specification Language for Heterogeneous Service Orchestration based on Process Calculus and Holonic Multi-agent Systems. -- Counterfactual Explanations for Sustainable Tourism Indicators. -- Tracking Healthy Organs in Medical Scans to Improve Cancer Treatment by Using UW-Madison GI Tract Image Segmentation. -- Low consumption models for disease diagnosis in isolated farms. -- Fast and Scalable Recommendation Retrieval Model with Mixed Attention and Knowledge Distillation. -- Federated Learning for Vietnamese SMS Spam Detection using Pre-Trained PhoBERT. -- Deep Learning Inference on Edge: A Preliminary Device Comparison. -- Causal Explanation of Graph Neural Networks. -- The contribution of social sciences driven user studies to the development of human-centered artificial intelligence. -- Towards Reliable Drift Detection and Explanation in Text Data. -- Using Diffusion Models for Data Augmentation on Limited Rodent OCT Datasets. -- Employing Explainable AI techniques for Air Pollution: An ante-hoc and post-hoc approach in dioxide nitrogen forecasting. -- Predicting employee attrition in a multi-company setting. -- A deep-learning approach for the identification of new subtypes of lung cancer . -- Loss Function Role in Processing Sequences with Heavy-Tailed Distributions. -- Cooperative-Competitive Decision-Making in Resource Management: A Reinforcement Learning Perspective. -- Improving Speech Emotion Recognition: Novel Aggregation Strategies for Self-Supervised Features. -- Refining Multiple Instance Learning with Attention Regularization for Whole Slide Image Classification. -- Evaluating performance and trustworthiness of RAG systems for generating administrative text. -- Blueprint of Tomorrow: Contrasting Off-line and On-line Drawing Tasks for Alzheimer's Disease Screening. -- Digital Mental Health Apps: Key Features and User Engagement for Better Wellness. -- Automatic PDF Document Classification with Machine Learning. -- Contributions on Mixtures of Polynomials for Hybrid Bayesian Networks. -- Age-unbiased Facial Emotion Recognition with Regularizing Self-attention Value Vector. -- Assessing the Impact of Temporal Data Aggregation on the Reliability of Predictive Machine Learning Models. -- Topic modeling in Telegram channels during the Russia-Ukraine conflict. -- Structural and Semantic Data Layers in Time Series Analyses.
• Sommario/riassunto: This two-volume set, LNCS 15346 and LNCS 15347, constitutes the proceedings of the 25th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2024, held in Valencia, ; Spain, during November 20–22, 2024. The 86 full papers and 6 short papers presented in this book were carefully reviewed and selected from 130 submissions. IDEAL 2024 is focusing on Big Data Analytics and Privacy, Machine Learning & Deep Learning for Real-World Applications, Data Mining and Pattern Recognition, Information Retrieval and Management, Bio and Neuro-Informatics, and Hybrid Intelligent Systems and Agents.