Neural network training method and device, electronic equipment and storage medium

Abstract

The invention relates to a neural network training method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the screening of a plurality of firstsample images, and determining a plurality of labeled second sample images from the plurality of first sample images; Generating a plurality of fourth sample images according to a third sample image marked as a first category in the plurality of second sample images, and marking the fourth sample image as the first category; And training the diagnosis network according to the plurality of labeledsecond sample images and the plurality of fourth sample images. The embodiment of the invention discloses a neural network training method. According to the method, the plurality of first sample images can be screened to obtain the labeled second sample image, the labeling cost can be reduced, the fourth sample image can be generated, the number of the samples of the first category can be increased, the total number of the samples can be increased, the number of the samples of the first category and the second category is balanced, and the training effect is improved.

Description

technical field [0001] The present disclosure relates to the field of computer technology, and in particular to a neural network training method and device, electronic equipment and storage media. Background technique [0002] In related technologies, in the process of training the neural network, the sample size may be insufficient and the cost of sample labeling may occur, resulting in poor training effect. For example, medical images need to be labeled by professional doctors, the cost is high, and healthy people seldom undergo medical examinations to obtain medical images, resulting in a small number of negative samples in medical images, which makes the number of positive and negative samples unbalanced, resulting in poor training effect. Difference. Contents of the invention [0003] The disclosure proposes a neural network training method and device, electronic equipment and a storage medium. [0004] According to an aspect of the present disclosure, a neural netw...

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Problems solved by technology

[0002] In related technologies, in the process of training the neural network, the sample size may be insufficient and the cost of sample labeling may occur, resulting in poor training effect

For example, medical images need to be labeled by professional doctors, the cost is high, and healthy people seldom undergo medical examinations to obtain medical images, resulting in a small number of negative samples in medical images, which makes the number of positive and negative samples unbalanced, resulting in poor training effect. Difference

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