Task model acquisition method and device, storage medium and electronic device

Abstract

The invention discloses a task model acquisition method and device, a storage medium and an electronic device. The method comprises the following steps: obtaining target model parameters obtained by carrying out model training on the first training model, wherein the first training model comprises: a first encoder and a first decoder, the target model parameters comprisea first model parameter corresponding to the first encoder, the input of the first training model is a first image of a first channel of the target optical image, the output of the trained first training model is a prediction image corresponding to a second image of a second channel of the target optical image, and the graph similarity between the prediction image and the second image is greater than or equal to a target similarity threshold; initializing model parameters of a second training model by using the target model parameters to obtain an initial task model, the second training model comprising a second encoderhaving the same structure as the first encoder; and training the initial task model by using the target optical image to obtain a target task model.

Description

technical field [0001] The present invention relates to the field of computers, in particular to a task model acquisition method and device, a storage medium and an electronic device. Background technique [0002] At present, when using a network model to perform optical image processing tasks, it is necessary to use sample optical images to perform model training on the initial network model to obtain a trained target network model. For example, network models such as CNN (Convolutional Neural Network, convolutional neural network), FCN (Fully Convolutional Network, fully convolutional network) can be used to perform tasks such as image classification and image segmentation. [0003] When performing model training, the network model is first assigned randomly generated initial model parameters (model parameters of the random initialization network model); the sample optical image is input into the randomly initialized network model, and the output results of the network mod...

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a task model acquisition method and device, a storage medium, and an electronic device, so as to at least solve the technical problems of slow model training convergence speed and poor model performance in the randomly initialized network model in the related art

Images