Patent ID: 11868904
Assignee: UNIVERSITY-INDUSTRY COOPERATION GROUP OF KYUNG HEE UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. A master apparatus comprising:
a hardware processor configured to
receive data from a slave apparatus,
generate a prediction model,
train the prediction model,
obtain the trained prediction model, and
transmit the prediction model or the trained prediction model to the slave apparatus; and

a hardware storage,
wherein the prediction model comprises:
a first prediction model configured to obtain a prediction result about a class corresponding to input data; and
a second prediction model configured to receive a result of the first prediction model and obtain a prediction result corresponding to the result of the first prediction model,

wherein the first prediction model comprises a first algorithm to which first data is input and a second algorithm to which an output result of the first algorithm is input,
wherein the hardware storage of the master apparatus is configured to store feedback information that includes information on training accuracy and learning loss of a respective model, and
wherein:
the first algorithm is implemented using a convolutional neural network (CNN), and the second algorithm is implemented using a recurrent neural network (RNN), which is designed for temporal dynamics of input sequential data and includes a plurality of RNN cells;
the first data is inputted to and then convolution-processed by the CNN of the first algorithm, second data, which is convolution result data, is acquired, and the second data is input to the RNN of the second algorithm; and
third data, which is output data of the RNN, is transferred to the second prediction model.