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Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2017; 26th International C Alessandra Lintas,Stefano Rovetta,Alessandro E.P. Confe

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發(fā)表于 2025-3-28 16:41:26 | 只看該作者
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發(fā)表于 2025-3-28 20:15:00 | 只看該作者
Conference proceedings 2017, held in Alghero, Italy, in September 2017...?..The 128 full papers included in this volume were carefully reviewed and selected from 270 submissions. They were organized in topical sections named: From Perception to Action; From Neurons to Networks; Brain Imaging; Recurrent Neural Networks; Neurom
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發(fā)表于 2025-3-29 00:02:35 | 只看該作者
0302-9743 e on Artificial Neural Networks, ICANN 2017, held in Alghero, Italy, in September 2017...?..The 128 full papers included in this volume were carefully reviewed and selected from 270 submissions. They were organized in topical sections named: From Perception to Action; From Neurons to Networks; Brain
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發(fā)表于 2025-3-29 04:47:19 | 只看該作者
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發(fā)表于 2025-3-29 07:55:54 | 只看該作者
https://doi.org/10.1007/978-3-531-91689-7k that is able to monitor drivers video surveillance, more specifically detect and classify when the driver is using a cell phone. The experiments show an impressive accuracy, achieving up 99% of accuracy detecting distracted driver.
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發(fā)表于 2025-3-29 14:29:51 | 只看該作者
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發(fā)表于 2025-3-29 19:01:50 | 只看該作者
A Deep Learning Approach to Detect Distracted Drivers Using a Mobile Phonek that is able to monitor drivers video surveillance, more specifically detect and classify when the driver is using a cell phone. The experiments show an impressive accuracy, achieving up 99% of accuracy detecting distracted driver.
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發(fā)表于 2025-3-29 22:50:39 | 只看該作者
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發(fā)表于 2025-3-30 03:29:20 | 只看該作者
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發(fā)表于 2025-3-30 06:47:52 | 只看該作者
https://doi.org/10.1007/978-3-531-91689-7earning classifiers: Convolutional and Recurrent Neural Networks. The implementation is realized on an Apache Spark engine, running on IBM Power8 servers. The experiments use real-world data from the Netbeans, Eclipse and Mozilla projects.
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