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Artificial Neural Networks and Machine Learning – ICANN 2021 : 30th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 14–17, 2021, Proceedings, Part IV - 1st ed. 2021

By: (Edited by) Igor Farkas , (Edited by) Paolo Masulli , (Edited by) Sebastian Otte , (Edited by) Stefan Wermter

Extended Catalogue

Ksh 16,200.00

Format: Paperback / Softback

ISBN-10: 3030863794

ISBN-13: 9783030863791

Edition: 1st ed. 2021

Series: Lecture Notes in Computer Science

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Sep 11th, 2021

Print length: 703 Pages

Product Classification: Educational equipment & technology, computer-aided learning (CAL)
Information technology: general issues
Business applications
Computer hardware
Artificial intelligence

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The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes. In this volume, the papers focus on topics such as model compression, multi-task and multi-label learning, neural network theory, normalization and regularization methods, person re-identification, recurrent neural networks, and reinforcement learning. *The conference was held online 2021 due to the COVID-19 pandemic.
The proceedings set LNCS 12891, LNCS 12892, LNCS 12893, LNCS 12894 and LNCS 12895 constitute the proceedings of the 30th International Conference on Artificial Neural Networks, ICANN 2021, held in Bratislava, Slovakia, in September 2021.* The total of 265 full papers presented in these proceedings was carefully reviewed and selected from 496 submissions, and organized in 5 volumes.

In this volume, the papers focus on topics such as model compression, multi-task and multi-label learning, neural network theory, normalization and regularization methods, person re-identification, recurrent neural networks, and reinforcement learning.

*The conference was held online 2021 due to the COVID-19 pandemic.

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