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Intelligent Data Engineering and Automated Learning – IDEAL 2025 : 26th International Conference, Jaén, Spain, November 13–15, 2025, Proceedings, Part II / / edited by Luis Martínez, David Camacho, Hujun Yin, Bapi Dutta, Raciel Yera, Rosa M. Rodríguez Domínguez, Antonio Tallón-Ballesteros



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Autore: Martinez Luis Visualizza persona
Titolo: Intelligent Data Engineering and Automated Learning – IDEAL 2025 : 26th International Conference, Jaén, Spain, November 13–15, 2025, Proceedings, Part II / / edited by Luis Martínez, David Camacho, Hujun Yin, Bapi Dutta, Raciel Yera, Rosa M. Rodríguez Domínguez, Antonio Tallón-Ballesteros Visualizza cluster
Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2026
Edizione: 1st ed. 2026.
Descrizione fisica: 1 online resource (840 pages)
Disciplina: 006.312
Soggetto topico: 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
Sommario/riassunto: This two-volume set, LNCS 16238 and LNCS 16239, constitutes the proceedings of the 26th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2025, which was held in Jaén, Spain, during November 13–15, 2025. The 83 full papers and 12 short papers included in the proceedings were carefully reviewed and selected from 146 submissions. The core themes of IDEAL 2025 included Trustworthy Artificial Intelligence and Generative AI, Aenetic AI, LLMs, Federated Learning, Machine Learning & Deep Learning for Real-World Applications, Data Mining and Pattern Recognition, Cybersecurity, Information Retrieval and Management, and Hybrid Intelligent Systems and Agents.
Titolo autorizzato: Intelligent Data Engineering and Automated Learning – IDEAL 2025  Visualizza cluster
ISBN: 3-032-10489-0
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 996691664003316
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Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 16239