Auto-Starting Semisupervised-Learning-Based Identification of Synchrophasor Data Anomalies
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3142103
Abstract: In Internet of Things (IoT)-enabled modern power grids, advanced IoT devices, e.g., synchronous phasor measurement units (PMUs), have been widely deployed to closely monitor the grids’ states and dynamics. In practice, however, PMU measurements are… read more here.
Keywords: auto starting; starting semisupervised; semisupervised learning; pmu ... See more keywords
Laplacian Welsch Regularization for Robust Semisupervised Learning.
Sign Up to like & getrecommendations! Published in 2020 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2019.2953337
Abstract: Semisupervised learning (SSL) has been widely used in numerous practical applications where the labeled training examples are inadequate while the unlabeled examples are abundant. Due to the scarcity of labeled examples, the performances of the… read more here.
Keywords: ssl; welsch regularization; semisupervised learning; welsch ... See more keywords
Semisupervised Learning-Based SAR ATR via Self-Consistent Augmentation
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2020.3013968
Abstract: In synthetic aperture radar (SAR) automatic target recognition, it is expensive and time-consuming to annotate the targets. Thus, training a network with a few labeled data and plenty of unlabeled data attracts attention of many… read more here.
Keywords: consistent augmentation; learning based; loss; augmentation ... See more keywords
A Semisupervised Learning Framework for Recognition and Classification of Defects in Transient Thermography Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2021.3101309
Abstract: The defect classification task is of great benefit to evaluating the safety performance of equipment and providing useful feedback information for discovering production process problems. In this article, we present a semisupervised learning (SSL) framework… read more here.
Keywords: framework; semisupervised learning; detection; transient thermography ... See more keywords
Intelligent Fault Diagnosis With Noisy Labels via Semisupervised Learning on Industrial Time Series
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3229130
Abstract: Deep neural networks (DNNs) excel at industrial fault diagnosis. Their performance heavily relies on the quality of human-annotated labels. Due to perception limitations of annotators, industrial time series samples (such as vibration and voltage signals)… read more here.
Keywords: time; fault diagnosis; time series; semisupervised learning ... See more keywords
Remote Sensing Image Classification with Few Labeled Data Using Semisupervised Learning
Sign Up to like & getrecommendations! Published in 2023 at "Wireless Communications and Mobile Computing"
DOI: 10.1155/2023/7724264
Abstract: Synthetic aperture radar (SAR) as an imaging radar is capable of high-resolution remote sensing, independent of flight altitude, and independent of weather. Traditional SAR ship image classification tends to extract features manually. It relies too… read more here.
Keywords: remote sensing; classification; semisupervised learning; image classification ... See more keywords
Parametric UMAP Embeddings for Representation and Semisupervised Learning
Sign Up to like & getrecommendations! Published in 2021 at "Neural Computation"
DOI: 10.1162/neco_a_01434
Abstract: Abstract UMAP is a nonparametric graph-based dimensionality reduction algorithm using applied Riemannian geometry and algebraic topology to find low-dimensional embeddings of structured data. The UMAP algorithm consists of two steps: (1) computing a graphical representation… read more here.
Keywords: learning parametric; parametric umap; umap embeddings; embeddings representation ... See more keywords