Artificial Neural Networks and Machine Learning – ICANN 2022 [[electronic resource] ] : 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings, Part I / / edited by Elias Pimenidis, Plamen Angelov, Chrisina Jayne, Antonios Papaleonidas, Mehmet Aydin

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
• Edizione: 1st ed. 2022.
• Descrizione fisica: 1 online resource (783 pages)
• Disciplina: 006.3
• Soggetto topico: Artificial intelligence; Application software; Computers; Computer engineering; Computer networks; Artificial Intelligence; Computer and Information Systems Applications; Computing Milieux; Computer Engineering and Networks
• Persona (resp. second.): PimenidisElias
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Deep Learning -- , Neural Network Theory -- Relational Learning, Reinforcement Learning -- Natural language processing, Generative Models -- Graphical Models, Recommender Systems -- Image Processing, Recurrent Networks -- Evolutionary Neural Networks -- Unsupervised Neural Networks -- Neural Network Models.
• Sommario/riassunto: Chapter “Sim-to-Real Neural Learning with Domain Randomisation for Humanoid Robot Grasping ” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
• Titolo autorizzato: Artificial neural networks and machine learning -- ICANN 2022
• ISBN: 3-031-15919-5
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996490365903316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 13529