Self-adaptive bit network quantization method and system and image processing method

Abstract

The invention discloses a self-adaptive bit network quantization method and system and an image processing method. The method comprises the following steps: acquiring a full-precision network model; obtaining a test data set under the applied classification task, and testing a classification result of the full-precision network model in the test data set; quantizing parameters of the full-precision network model by using a quantization function, and calculating standard errors of different parameters before and after quantization under a bit width condition to be selected; estimating the influence of the quantization of different parameters on the network performance, and obtaining the importance of the current parameter; solving a bit width allocation strategy with the highest accuracy under the target compression ratio; and quantizing the network according to a bit width distribution strategy to obtain a final network for image classification and target detection. According to the invention, the bit width and the quantization model of the network parameters under different compression rate requirements can be quickly given, meanwhile, high classification accuracy is ensured, and the universality of the quantization method is ensured.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an adaptive bit network quantization method, system and image processing method. Background technique [0002] Image is the main medium for human beings to obtain and exchange information, and the development of image processing technology has profoundly affected people's production and life. Especially in the 21st century, with the expansion of the scope of human activities and the advancement of imaging technology, the quantity and quality of image data have achieved great growth, so the intelligent processing of image data has received more and more attention. At present, the main image processing tasks include classification, which is to judge the main target contained in the picture; and target recognition, which is to locate the position of a specific type of object in the picture. Traditional image classification and object recognition methods need to manually de...

AI Technical Summary

Problems solved by technology

The existing adaptive bit width allocation methods include network structure search and performance estimation. The search-based method needs a lot of time and resources to train a super network, while the existing performance estimation-based method can only be applied to online quantization. function and poor performance

Images