Patent ID: 11966836
Assignee: KABUSHIKI KAISHA TOSHIBA
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 4:
5. The system according to claim 4, wherein
the recurrent neural network further includes a third recurrent neural network part including a third output layer,
outputs of the first recurrent neural network part and the second recurrent neural network part are input to the third recurrent neural network part,
the circuitry trains the third recurrent neural network part by inputting the first data and the fourth data respectively to the first recurrent neural network part and the second recurrent neural network part, the third output layer including a fifth neuron and a sixth neuron, a fifth value corresponding to an action of a combination of the first body part and the second body part of the first proficiency being set as teacher data in the fifth neuron,
the circuitry trains the third recurrent neural network part by inputting the second data and the fifth data respectively to the first recurrent neural network part and the second recurrent neural network part, a sixth value corresponding to an action of the combination of the first body part and the second body part of the second proficiency being set as teacher data in the sixth neuron,
the circuitry inputs the third data and the sixth data respectively to the first recurrent neural network part and the second recurrent neural network part, and
the circuitry detects that at least part of the action of the third worker corresponds to the first proficiency when a fifth activity of the fifth neuron is larger than the threshold and detects that at least part of the action of the third worker corresponds to the second proficiency when a sixth activity of the sixth neuron is larger than the threshold.