Extreme Learning Machine for Joint Embedding and Clustering
Sign Up to like & getrecommendations! Published in 2018 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.01.115
Abstract: Abstract Clustering generic data, i.e., data not specific to a particular field, is a challenging problem due to their diverse complex structures in the original feature space. Traditional approaches address this problem by complementing clustering… read more here.
Keywords: machine joint; feature; extreme learning; learning machine ... See more keywords
Superimposition of Cone-Beam Computed Tomography Images by Joint Embedding
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Biomedical Engineering"
DOI: 10.1109/tbme.2016.2598584
Abstract: Objective: The superimposition of cone-beam computed tomography (CBCT) images is an essential step to evaluate shape variations of pre and postorthodontic operations due to pose variations and the bony growth. The aim of this paper… read more here.
Keywords: superimposition cone; beam computed; superimposition; joint embedding ... See more keywords
Fusing Multiview Functional Brain Networks by Joint Embedding for Brain Disease Identification
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Personalized Medicine"
DOI: 10.3390/jpm13020251
Abstract: Background: Functional brain networks (FBNs) derived from resting-state functional MRI (rs-fMRI) have shown great potential in identifying brain disorders, such as autistic spectrum disorder (ASD). Therefore, many FBN estimation methods have been proposed in recent… read more here.
Keywords: identification; functional brain; brain; multiview ... See more keywords