Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation
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| Titel: | Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation |
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| Beschreibung: | The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. |
| Autoren: | Igor V. Tetko, Věra Kůrková, Pavel Karpov, Fabian Theis |
| Resource Type: | eBook. |
| Schlagworte: | Artificial intelligence, Computer vision, Computer engineering, Computer networks, Algorithms, Data protection |
| Categories: | COMPUTERS / Artificial Intelligence / General, COMPUTERS / Artificial Intelligence / Computer Vision & Pattern Recognition, COMPUTERS / Networking / General, COMPUTERS / Programming / Algorithms, COMPUTERS / Security / General, COMPUTERS / Hardware / General |
| Datenbank: | eBook Index |
| Abstract: | The proceedings set LNCS 11727, 11728, 11729, 11730, and 11731 constitute the proceedings of the 28th International Conference on Artificial Neural Networks, ICANN 2019, held in Munich, Germany, in September 2019. The total of 277 full papers and 43 short papers presented in these proceedings was carefully reviewed and selected from 494 submissions. They were organized in 5 volumes focusing on theoretical neural computation; deep learning; image processing; text and time series; and workshop and special sessions. |
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| ISBN: | 9783030304867 9783030304874 |