A System of Searching the Channel Expansion Parameter for the Speed-up of Inverted Residual Block and the method thereof for low specification embedded system and the method thereof

摘要

The present invention relates to a system and method to set a channel extension parameter of an inverted residual block for the calculation of a convolutional neural network in a low-specification embedded environment, capable of setting an optimal channel extension parameter by conducting a test while changing the value of a channel extension parameter in an inverted residual block and analyzing the result of the test result. The system includes: a neural network model part storing a convolutional neural network model; a test set storage part for storing a data set for learning or testing the convolutional neural network model; a parameter changing part changing the value of a channel extension parameters in an inverted residual block of the convolutional neural network model; a learning testing part learning and testing the convolutional neural network model to which the changed parameter has been reflected; and an analyzing part collecting a test result of the convolutional neural network model, and analyzing the collected result to detect an optimal parameter. Therefore, when compared to existing technology, a decrease in accuracy can be less than 1% while model lightening and calculation speed can be improved by approximately 40%.