Pre-labeling model training method and device, certificate pre-labeling method and device, equipment and medium

Abstract

The invention relates to the field of classification models of artificial intelligence, and provides a pre-labeling model training method and device, a certificate pre-labeling method and device, equipment and a medium. The method comprises the steps: obtaining a target labeling category, target description, model performance parameters and an image sample set; crawling a to-be-migrated category in a target classification and identification library by using a text similarity technology; searching a to-be-migrated model from the target classification and identification library through a simulation target identification technology, and identifying a target region of each image sample; performing target fine tuning to obtain a fine tuning area, and inputting the image sample, the fine tuning area and the target labeling category into the to-be-migrated model; acquiring and marking a target labeling area by using a transfer learning technology; determining a loss value according to the target labeling area and the fine tuning area; and training the to-be-migrated model until the training is completed to obtain a pre-labeled model. According to the invention, automatic training of a zero-labeling image sample set is realized, the pre-labeling model is obtained, and the manual labeling time and workload are reduced.

Description

technical field [0001] The present invention relates to the field of classification models of artificial intelligence, in particular to a pre-marking model training, a certificate pre-marking method, a device, a computer device and a storage medium. Background technique [0002] Artificial intelligence technology is a comprehensive subject that involves a wide range of fields, including both hardware-level technology and software-level technology. Artificial intelligence software technology mainly includes several major directions such as computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning. Among them, computer vision technology (CV, Computer Vision) is a science that studies how to make machines "see", usually including image processing, image recognition, image semantic understanding, image retrieval, optical character recognition (OCR, Optical Character Recognition) ) and other technologies....

AI Technical Summary

Problems solved by technology

In order to obtain an image recognition model with higher recognition accuracy, it is necessary to train the image recognition model through a large number of labeled samples. In the prior art, when constructing training samples, manual input and other manual labeling methods are usually used, which not only consumes The labor cost also greatly reduces the labeling efficiency of samples, which brings great difficulties to model training.

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