Availability: Artificial neural networks and machine learning – ICANN 2022

Artificial neural networks and machine learning – ICANN 2022: 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III

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Bibliographic Details
Corporate Author:	ICANN (Veranstaltung) Bristol (Author)
Other Authors:	Pimenidis, Elias (Editor), Angelov, Plamen P. 1966- (Editor), Jayne, Chrisina (Editor), Papaleonidas, Antonios (Editor), Aydin, Mehmet (Editor)
Format:	Electronic Conference Proceedings eBook
Language:	English
Published:	Cham, Switzerland Springer [2022]
Series:	Lecture notes in computer science 13531
Subjects:	Artificial Intelligence Computer and Information Systems Applications Computer Imaging, Vision, Pattern Recognition and Graphics Computer Engineering and Networks Artificial intelligence Application software Image processing—Digital techniques Computer vision Computer engineering Computer networks Gehirn Nervennetz Modell Neuronales Netz Maschinelles Lernen Anwendung Konferenzschrift > 2022 > Bristol
Links:	https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3 https://doi.org/10.1007/978-3-031-15934-3
Physical Description:	1 Online-Ressource (xxii, 813 Seiten) 312 Illustrationen, 280 in Farbe
ISBN:	9783031159343
ISSN:	1611-3349
DOI:	10.1007/978-3-031-15934-3

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genre	(DE-588)1071861417 Konferenzschrift 2022 Bristol gnd-content
genre_facet	Konferenzschrift 2022 Bristol
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indexdate	2025-03-12T17:00:28Z
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isbn	9783031159343
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language	English
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physical	1 Online-Ressource (xxii, 813 Seiten) 312 Illustrationen, 280 in Farbe
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series2	Lecture notes in computer science
spellingShingle	Artificial neural networks and machine learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III Lecture notes in computer science Artificial Intelligence Computer and Information Systems Applications Computer Imaging, Vision, Pattern Recognition and Graphics Computer Engineering and Networks Artificial intelligence Application software Image processing—Digital techniques Computer vision Computer engineering Computer networks Gehirn (DE-588)4019752-9 gnd Nervennetz (DE-588)4041638-0 gnd Modell (DE-588)4039798-1 gnd Neuronales Netz (DE-588)4226127-2 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Anwendung (DE-588)4196864-5 gnd
subject_GND	(DE-588)4019752-9 (DE-588)4041638-0 (DE-588)4039798-1 (DE-588)4226127-2 (DE-588)4193754-5 (DE-588)4196864-5 (DE-588)1071861417
title	Artificial neural networks and machine learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III
title_auth	Artificial neural networks and machine learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III
title_exact_search	Artificial neural networks and machine learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III
title_full	Artificial neural networks and machine learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III Elias Pimenidis, Plamen Angelov, Chrisina Jayne, Antonios Papaleonidas, Mehmet Aydin (eds.)
title_fullStr	Artificial neural networks and machine learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III Elias Pimenidis, Plamen Angelov, Chrisina Jayne, Antonios Papaleonidas, Mehmet Aydin (eds.)
title_full_unstemmed	Artificial neural networks and machine learning – ICANN 2022 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III Elias Pimenidis, Plamen Angelov, Chrisina Jayne, Antonios Papaleonidas, Mehmet Aydin (eds.)
title_short	Artificial neural networks and machine learning – ICANN 2022
title_sort	artificial neural networks and machine learning icann 2022 31st international conference on artificial neural networks bristol uk september 6 9 2022 proceedings part iii
title_sub	31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022 : proceedings, part III
topic	Artificial Intelligence Computer and Information Systems Applications Computer Imaging, Vision, Pattern Recognition and Graphics Computer Engineering and Networks Artificial intelligence Application software Image processing—Digital techniques Computer vision Computer engineering Computer networks Gehirn (DE-588)4019752-9 gnd Nervennetz (DE-588)4041638-0 gnd Modell (DE-588)4039798-1 gnd Neuronales Netz (DE-588)4226127-2 gnd Maschinelles Lernen (DE-588)4193754-5 gnd Anwendung (DE-588)4196864-5 gnd
topic_facet	Artificial Intelligence Computer and Information Systems Applications Computer Imaging, Vision, Pattern Recognition and Graphics Computer Engineering and Networks Artificial intelligence Application software Image processing—Digital techniques Computer vision Computer engineering Computer networks Gehirn Nervennetz Modell Neuronales Netz Maschinelles Lernen Anwendung Konferenzschrift 2022 Bristol
url	https://doi.org/10.1007/978-3-031-15934-3
volume_link	(DE-604)BV014880109
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