METHOD AND DEVICE FOR QUANTIZING DEEP LEARNING NEURAL NETWORK MODEL BY CONSIDERING CHANGE IN EXTERNAL ENVIRONMENT
개요
발명자
Won Jae LEE; Ji Eun LIM
IPC 분류
CPC 분류
A quantization method of a deep learning neural network model is disclosed. An embodiment of the disclosure provides a quantization method comprising: detecting a feature change of input data caused by a change in an external environment, from input image data of a quantized deep learning neural network model based on a plurality of preset quantization parameters; performing quantization calibration for the deep learning neural network model to determine a new quantization parameter corresponding to the feature change of input data caused by the change in the external environment; and updating at least one of the plurality of preset quantization parameters based on the new quantization parameter.
원문 (중국어)
A quantization method of a deep learning neural network model is disclosed. An embodiment of the disclosure provides a quantization method comprising: detecting a feature change of input data caused by a change in an external environment, from input image data of a quantized deep learning neural network model based on a plurality of preset quantization parameters; performing quantization calibration for the deep learning neural network model to determine a new quantization parameter corresponding to the feature change of input data caused by the change in the external environment; and updating at least one of the plurality of preset quantization parameters based on the new quantization parameter.