Shuai Yuan, Junhai Qiu, Hongxia Xu, Yan Zhang, Jiaxing Zhang
{"title":"Few-shot segmentation based on multi-level and cross-scale clustering","authors":"Shuai Yuan, Junhai Qiu, Hongxia Xu, Yan Zhang, Jiaxing Zhang","doi":"10.1080/09540091.2023.2287972","DOIUrl":null,"url":null,"abstract":"The problem of image segmentation with few-shot learning is addressed in this paper, which is a challenging task due to the lack of sufficient high-precision annotated data. A novel method that con...","PeriodicalId":50629,"journal":{"name":"Connection Science","volume":"32 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Connection Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09540091.2023.2287972","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The problem of image segmentation with few-shot learning is addressed in this paper, which is a challenging task due to the lack of sufficient high-precision annotated data. A novel method that con...
期刊介绍：
Connection Science is an interdisciplinary journal dedicated to exploring the convergence of the analytic and synthetic sciences, including neuroscience, computational modelling, artificial intelligence, machine learning, deep learning, Database, Big Data, quantum computing, Blockchain, Zero-Knowledge, Internet of Things, Cybersecurity, and parallel and distributed computing.
A strong focus is on the articles arising from connectionist, probabilistic, dynamical, or evolutionary approaches in aspects of Computer Science, applied applications, and systems-level computational subjects that seek to understand models in science and engineering.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
