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Artificial Neural Networks and Machine Learning – ICANN 2022: 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings, Part II de Elias Pimenidis

Artificial Neural Networks and Machine Learning – ICANN 2022: 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings, Part II: Lecture Notes in Computer Science, cartea 13530

Editat de Elias Pimenidis, Plamen Angelov, Chrisina Jayne, Antonios Papaleonidas, Mehmet Aydin
en Limba Engleză Paperback – 7 sep 2022
The 4-volumes set of LNCS 13529, 13530, 13531, and 13532 constitutes the proceedings of the 31st International Conference on Artificial Neural Networks, ICANN 2022, held in Bristol, UK, in September 2022.
The total of 255 full papers presented in these proceedings was carefully reviewed and selected from 561 submissions. ICANN 2022 is a dual-track conference featuring tracks in brain inspired computing and machine learning and artificial neural networks, with strong cross-disciplinary interactions and applications. Chapters “Learning Flexible Translation Between Robot Actions and Language Descriptions”, “Learning Visually Grounded Human-Robot Dialog in a Hybrid Neural Architecture” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
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Specificații

ISBN-13: 9783031159305
ISBN-10: 3031159306
Pagini: 813
Ilustrații: XXII, 813 p. 247 illus., 220 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.15 kg
Ediția:1st ed. 2022
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Textul de pe ultima copertă

Chapters “Learning Flexible Translation Between Robot Actions and Language Descriptions”, “Learning Visually Grounded Human-Robot Dialog in a Hybrid Neural Architecture” are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Cuprins

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.