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기록

MODEL TRAINING METHOD, IMAGE PROCESSING METHOD, ELECTRONIC DEVICE AND STORAGE MEDIUM

발명심사 중
1조회수
22청구항 · 5 독립항
§ Ⅰ

개요

발명자

Xiaojie JIN; Zhicheng HUANG; Jiashi FENG

IPC 분류

G6V 10/82G6V 10/74G6V 10/80

CPC 분류

G6V10/82G6V10/761G6V10/80

The present disclosure provides a model training method and apparatus, and an electronic device; and the method includes: acquiring a first sample image, which includes a first image block which is uncovered and an second image block which is covered; processing the first sample image through a first model, to obtain a first image feature corresponding to the first image block; reconstructing the second image block according to the first image feature, to obtain a first image, and determining a fusion prediction feature of the first image block and the second image block, according to the first image feature; acquiring a target image feature in a target image, the target image being an image after preprocessing of the first sample image; and updating a model parameter of the first model, according to the first image, the second image block, the fusion prediction feature and the target image feature.

원문 (중국어)

The present disclosure provides a model training method and apparatus, and an electronic device; and the method includes: acquiring a first sample image, which includes a first image block which is uncovered and an second image block which is covered; processing the first sample image through a first model, to obtain a first image feature corresponding to the first image block; reconstructing the second image block according to the first image feature, to obtain a first image, and determining a fusion prediction feature of the first image block and the second image block, according to the first image feature; acquiring a target image feature in a target image, the target image being an image after preprocessing of the first sample image; and updating a model parameter of the first model, according to the first image, the second image block, the fusion prediction feature and the target image feature.