Hyperspectral Imagery Classification Based on Contrastive Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3139099
Abstract: Supervised machine learning and deep learning methods perform well in hyperspectral image classification. However, hyperspectral images have few labeled samples, which make them difficult to be trained because supervised classification methods rely heavily on sample… read more here.
Keywords: classification; self supervised; imagery classification; hyperspectral imagery ... See more keywords
A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2019.2938295
Abstract: One of the challenges in motor imagery (MI) classification tasks is finding an easy-handled electroencephalogram (EEG) representation method which can preserve not only temporal features but also spatial ones. To fully utilize the features on… read more here.
Keywords: motor imagery; imagery classification; multi branch; eeg ... See more keywords
Efficient CSP Algorithm With Spatio-Temporal Filtering for Motor Imagery Classification
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2020.2979464
Abstract: Common spatial pattern (CSP) is an efficient algorithm widely used in feature extraction of EEG-based motor imagery classification. Traditional CSP depends only on spatial filtering, that aims to maximize or minimize the ratio of variances… read more here.
Keywords: csp; motor imagery; imagery classification; spatio temporal ... See more keywords
Regularized RKHS-Based Subspace Learning for Motor Imagery Classification
Sign Up to like & getrecommendations! Published in 2022 at "Entropy"
DOI: 10.3390/e24020195
Abstract: Brain–computer interface (BCI) technology allows people with disabilities to communicate with the physical environment. One of the most promising signals is the non-invasive electroencephalogram (EEG) signal. However, due to the non-stationary nature of EEGs, a… read more here.
Keywords: subspace; imagery classification; rkhs subspace; classification ... See more keywords