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

A task model and acquisition method technology, applied in the computer field, can solve problems such as slow convergence speed of model training and poor model performance, and achieve the effect of solving slow convergence speed of model training, ensuring model performance, and improving convergence speed

Active Publication Date: 2019-10-22
腾讯医疗健康(深圳)有限公司
View PDF6 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Task model acquisition method and device, storage medium and electronic device
  • Task model acquisition method and device, storage medium and electronic device
  • Task model acquisition method and device, storage medium and electronic device

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0140] As an optional implementation, the input module includes:

[0141] (1) The extraction sub-module is used to extract the target image features from the first image using the first encoder;

[0142] (2) The processing sub-module is used to process the target image features using the target pooling layer and the target fully connected layer to obtain target prediction information. Among them, the target pooling layer and the target fully connected layer are located in the first encoder and the first encoder. Between decoders, the target prediction information is used to indicate the predicted distribution of the pixel value of each pixel in the second image in multiple pixel value intervals;

[0143] (3) The input sub-module is used to input the target image characteristics and target prediction information to the first decoder to obtain the first prediction image.

[0144] Through this embodiment, by setting an average pooling layer and a fully connected layer between the first e...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06N3/08G06N3/04G16H30/00
CPCG06N3/082G16H30/00G06N3/045
Inventor 李悦翔郑冶枫
Owner 腾讯医疗健康(深圳)有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap