Graph Embedding and Distribution Alignment for Domain Adaptation in Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2021.3099805
Abstract: Recent studies in cross-domain classification have shown that discriminant information of both source and target domains is very important. In this article, we propose a new domain adaptation (DA) method for hyperspectral image (HSI) classification,… read more here.
Keywords: alignment; domain; classification; distribution alignment ... See more keywords
Distribution Alignment and Discriminative Feature Learning for Domain Adaptation in Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3128590
Abstract: Domain adaptation (DA) aims to use a well-labeled source domain to predict the labels of the unlabeled or poor-labeled target domain. Most of the existing DA methods focus on the use of feature-level or sample-level… read more here.
Keywords: information; domain adaptation; distribution alignment; classification ... See more keywords
Deep Joint Distribution Alignment: A Novel Enhanced-Domain Adaptation Mechanism for Fault Transfer Diagnosis
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2022.3162957
Abstract: Various domain adaptation (DA) methods have been proposed to address distribution discrepancy and knowledge transfer between the source and target domains. However, many DA models focus on matching the marginal distributions of two domains and… read more here.
Keywords: joint distribution; distribution alignment; transfer; fault ... See more keywords
Adaptive Feature Projection With Distribution Alignment for Deep Incomplete Multi-View Clustering
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Image Processing"
DOI: 10.1109/tip.2023.3243521
Abstract: Incomplete multi-view clustering (IMVC) analysis, where some views of multi-view data usually have missing data, has attracted increasing attention. However, existing IMVC methods still have two issues: 1) they pay much attention to imputing or… read more here.
Keywords: incomplete multi; distribution alignment; multi view; feature ... See more keywords