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Coles Artificial Neural Networks and Machine Learning - ICANN 2021: 30th International Conference on Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part II at Bayshore Shopping Centre in Ottawa, ON
Artificial Neural Networks and Machine Learning - ICANN 2021: 30th International Conference on Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part II
Artificial Neural Networks and Machine Learning - ICANN 2021: 30th International Conference on Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part II in Ottawa, ON
Artificial Neural Networks and Machine Learning - ICANN 2021: 30th International Conference on Networks, Bratislava, Slovakia, September 14-17, 2021, Proceedings, Part II in Ottawa, ON
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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 computer vision and object detection, convolutional neural networks and kernel methods, deep learning and optimization, distributed and continual learning, explainable methods, few-shot learning and generative adversarial networks. *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 computer vision and object detection, convolutional neural networks and kernel methods, deep learning and optimization, distributed and continual learning, explainable methods, few-shot learning and generative adversarial networks. *The conference was held online 2021 due to the COVID-19 pandemic.
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