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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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樓主: Spouse
61#
發(fā)表于 2025-4-1 05:11:31 | 只看該作者
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發(fā)表于 2025-4-1 08:54:03 | 只看該作者
Towards an Accurate Identification of Pyloric Neuron Activity with VSDicomputationally exacting task that requires the development of sophisticated signal processing procedures to analyse the tri-phasic pyloric patterns generated by these neurons. This paper presents our work towards commissioning such procedures. The results achieved to date are most encouraging.
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發(fā)表于 2025-4-1 12:02:13 | 只看該作者
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發(fā)表于 2025-4-1 15:37:31 | 只看該作者
https://doi.org/10.1007/978-3-322-90299-3 interaction with the environment based on initial motor abilities. Supervised end-to-end learning of visuomotor skills is realized with a deep convolutional neural architecture that combines two important subtasks of grasping: object localization and inverse kinematics.
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發(fā)表于 2025-4-1 20:32:24 | 只看該作者
https://doi.org/10.1007/978-3-322-90299-3as observation. In the simulation environment reproducing the experimental environment, we confirmed that the learning converged to a state where it can reach the goal while avoiding obstacles with the minimum steps. Moreover, even in the real environment, it was confirmed that the robot can reach the goal while avoiding obstacles.
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