公开(公告)号：US20190340504A1

公开(公告)日：2019-11-07

申请号：US16244644

申请日：2019-01-10

Applicant: Samsung Electronics Co., Ltd.

Inventor： Junhaeng LEE ,  Hyunsun PARK ,  Sehwan LEE ,  Seungwon LEE

IPC: G06N3/08

Abstract: A neural network method and apparatus is provided. A processor-implemented neural network method includes determining, based on a determined number of classes of input data, a precision for a neural network layer outputting an operation result, and processing parameters of the layer according to the determined precision.

公开(公告)号：US20190042948A1

公开(公告)日：2019-02-07

申请号：US16051788

申请日：2018-08-01

Applicant: Samsung Electronics Co., Ltd.

Inventor： Junhaeng LEE ,  Seungwon LEE ,  Sangwon HA ,  Wonjo LEE

IPC: G06N3/10 ,  G06N3/04 ,  G06F7/544

Abstract: A method of generating a fixed-point quantized neural network includes analyzing a statistical distribution for each channel of floating-point parameter values of feature maps and a kernel for each channel from data of a pre-trained floating-point neural network, determining a fixed-point expression of each of the parameters for each channel statistically covering a distribution range of the floating-point parameter values based on the statistical distribution for each channel, determining fractional lengths of a bias and a weight for each channel among the parameters of the fixed-point expression for each channel based on a result of performing a convolution operation, and generating a fixed-point quantized neural network in which the bias and the weight for each channel have the determined fractional lengths.