Self-labeling techniques for semi-supervised time series classification: an empirical study
Sign Up to like & getrecommendations! Published in 2017 at "Knowledge and Information Systems"
DOI: 10.1007/s10115-017-1090-9
Abstract: An increasing amount of unlabeled time series data available render the semi-supervised paradigm a suitable approach to tackle classification problems with a reduced quantity of labeled data. Self-labeled techniques stand out from semi-supervised classification methods… read more here.
Keywords: self labeled; classification; time series; semi supervised ... See more keywords
Constructing Self-Labeled Materials Imaging Datasets from Open Access Scientific Journals with EXSCLAIM!
Sign Up to like & getrecommendations! Published in 2020 at "Microscopy and Microanalysis"
DOI: 10.1017/s1431927620023806
Abstract: Due to recent improvements in image resolution and acquisition speeds, materials microscopy is experiencing an explosion in imaging data. Yet, despite the volume of images generated, the overall accessibility landscape is highly fragmented, as researchers… read more here.
Keywords: materials imaging; microscopy; labeled materials; imaging datasets ... See more keywords
A Highly Accurate Framework for Self-Labeled Semisupervised Classification in Industrial Applications
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2017.2737827
Abstract: Self-labeled technique, a paradigm of semisupervised classification (SSC), is highly effective in alleviating the shortage of labeled data in classification tasks via an iterative self-labeling process. Although existing self-labeled SSC models show great prospect in… read more here.
Keywords: semisupervised classification; framework; self; self labeled ... See more keywords