Artificial neural networks and machine learning -- ICANN 2022 : 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022, Proceedings. Part I

Artificial neural networks and machine learning -- ICANN 2022 : Part I / 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6-9, 2022, Proceedings. Elias Pimenidis, Plamen Angelov, Chrisina Jayne, Antonios Papaleonidas, Mehmet Aydin (eds.).

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...

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Bibliographic Details
Corporate Author: International Conference on Artificial Neural Networks (European Neural Network Society) Bristol, England ; Online)
Other Authors: Pimenidis, Elias, Angelov, Plamen P., Jayne, Chrisina, Papaleonidas, Antonios, Aydin, M. E. (Mehmet E.)
Format: eBook
Language:English
Published: Cham : Springer, 2022.
Series:Lecture notes in computer science ; 13529.
Subjects:
Neural networks (Computer science) > Congresses.
Machine learning > Congresses.
Artificial intelligence > Congresses.
Artificial intelligence
Machine learning
Neural networks (Computer science)
Electronic books.
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congrès.
Online Access:Click for online access
Description
Summary: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.
Item Description:2 Related Work
Includes author index.
Physical Description:1 online resource (783 pages)
Bibliography:References-Brain Tumor Segmentation Framework Based on Edge Cloud Cooperation and Deep Learning-1 Introduction-2 Related Works-3 Methods-3.1 The Workflow of ECC-BTSD-3.2 The Edge End of ECC-BTSD-3.3 The Cloud End of ECC-BTSD-4 Experiments-4.1 The Dataset and Preprocessing-4.2 Performance of ECC-BSTD in the Offline Mode-4.3 Performance of ECC-BSTD in the Online Mode-4.4 ECC-BSTD Analysis Under Edge-Cloud Collaboration-5 Conclusion-References-CLTS+: A New Chinese Long Text Summarization Dataset with Abstractive Summaries-1 Introduction
ISBN:9783031159190
3031159195
9788303115911
830311591X
Source of Description, Etc. Note:Online resource; title from PDF title page (SpringerLink, viewed September 14, 2022).

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