Patent ID: 11907834
Assignee: DEEPMENTOR INC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method for establishing a data-recognition model, the method being implemented by a computer system that stores a deep neural network (DNN) and a set of a number (X) of dithering algorithms, where X≥2, the method comprising steps of:
A) generating a number (Z) of Y-combinations of dithering algorithms from the set of the number (X) of dithering algorithms, each of the Y-combinations including a number (Y) of dithering algorithms, where 1≤Y≤(X−1) and the number (Z) is equal to xCy;
B) for each of the number (Z) of Y-combinations of dithering algorithms, using the number (Y) of dithering algorithms of the Y-combination to perform a dithering operation on a to-be-processed data group represented in (a) number of bit(s), so as to obtain, in total, a number (Z) of size-reduced data groups each being represented in (b) number of bit(s), where 1≤b≤(a−1);
C) performing a number (Z) of training operations on the DNN using the number (Z) of size-reduced data groups, respectively, so as to generate, for each of the number (Z) of training operations, a DNN model, a training result of the training operation, and a steady deviation between the training result and a predetermined expectation; and
D) selecting one of the number (Z) of Y-combinations of dithering algorithms corresponding to the size-reduced data group that results in the training result with the smallest steady deviation as a filter module, selecting the corresponding DNN model as the data-recognition model, and generating layout of logic circuits hardware corresponding to the established data-recognition model.