Whole Slide Image Multi-Classification of Cervical Epithelial Lesions Based on Unsupervised Pre-training

Minfan ZhaoMin LingZhaohui WangJun ShiHongyu KanWenting HanHong An

机器学习系统方向论文：Whole Slide Image Multi-Classification of Cervical Epithelial Lesions Ba

↗在线页面Official page ◇DOI

内容导读Reading note

分类与摘要Category & abstract

将机器学习用于性能建模、训练系统或主动学习，连接算法与系统实现。

Metadata

完整论文信息Full record

title: Whole Slide Image Multi-Classification of Cervical Epithelial Lesions Based on Unsupervised Pre-training
title_zh: 待补充
abstract: 待补充
abstract_zh: 待补充
keywords: 学位认定 B, CCF B
year: 2022
published_date: 待补充
online_date: 待补充
paper_type: Conference
publication_status: Published
volume: 待补充
issue: 待补充
pages: 待补充
article_number: 待补充
publisher: IEEE
doi: 10.1109/embc48229.2022.9871149
research_area: 机器学习系统
tags: 学位认定 B, CCF B
category: 机器学习系统
summary: 将机器学习用于性能建模、训练系统或主动学习，连接算法与系统实现。
authors: Minfan Zhao, Min Ling, Zhaohui Wang, Jun Shi, Hongyu Kan, Wenting Han, Hong An
corresponding_authors: 待补充
affiliations: 待补充
funding: 待补充

Research area

机器学习系统

Citation

Minfan Zhao*, Min Ling, Zhaohui Wang, Jun Shi, Hongyu Kan，Wenting Han*, Hong An，Whole Slide Image Multi-Classification of Cervical Epithelial Lesions Based on Unsupervised Pre-training，in the proceeding of 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Scotland UK, July 11-15, 2022（CCF B）

BibTeX

@article{acsa2022_53,
  title = {Whole Slide Image Multi-Classification of Cervical Epithelial Lesions Based on Unsupervised Pre-training},
  year = {2022},
  doi = {10.1109/embc48229.2022.9871149}
}