Enhanced Deformation Vector Field Generation With Diffusion Models and Mamba‐Based Network for Registration Performance Enhancement
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.23171
Abstract: Recent advancements in deformable image registration (DIR) have seen the emergence of supervised and unsupervised deep learning techniques. However, supervised methods are limited by the quality of deformation vector fields (DVFs), while unsupervised approaches often… read more here.
Keywords: registration; supervised unsupervised; generation; deformation vector ... See more keywords
Comparative evaluation of supervised and unsupervised deep learning strategies for denoising hyperpolarized 129Xe lung MRI
Sign Up to like & getrecommendations! Published in 2025 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.70033
Abstract: Reduced signal‐to‐noise ratio (SNR) in hyperpolarized 129Xe MR images can affect accurate quantification for research and diagnostic evaluations. Thus, this study explores the application of supervised deep learning (DL) denoising, traditional (Trad) and Noise2Noise (N2N)… read more here.
Keywords: deep learning; supervised unsupervised; evaluation supervised; comparative evaluation ... See more keywords
Cross-domain person re-identification by hybrid supervised and unsupervised learning
Sign Up to like & getrecommendations! Published in 2021 at "Applied Intelligence"
DOI: 10.1007/s10489-021-02551-8
Abstract: Although the single-domain person re-identification (Re-ID) method has achieved great accuracy, the dependence on the label in the same image domain severely limits the scalability of this method. Therefore, cross-domain Re-ID has received more and… read more here.
Keywords: cross domain; unsupervised learning; domain; supervised unsupervised ... See more keywords
Generalized Feature Embedding for Supervised, Unsupervised, and Online Learning Tasks
Sign Up to like & getrecommendations! Published in 2019 at "Information Systems Frontiers"
DOI: 10.1007/s10796-018-9850-y
Abstract: Feature embedding is an emerging research area which intends to transform features from the original space into a new space to support effective learning. Many feature embedding algorithms exist, but they often suffer from several… read more here.
Keywords: supervised unsupervised; learning tasks; feature; online learning ... See more keywords
A unified distributed ELM framework with supervised, semi-supervised and unsupervised big data learning
Sign Up to like & getrecommendations! Published in 2019 at "Memetic Computing"
DOI: 10.1007/s12293-018-0271-8
Abstract: Extreme learning machine (ELM) as well as its variants have been widely used in many fields for its good generalization performance and fast learning speed. Though distributed ELM can sufficiently process large-scale labeled training data,… read more here.
Keywords: distributed elm; supervised unsupervised; supervised semi; semi supervised ... See more keywords
Supervised and unsupervised mapping of binary variables: a proximity perspective
Sign Up to like & getrecommendations! Published in 2024 at "Behaviormetrika"
DOI: 10.1007/s41237-024-00248-z
Abstract: We propose a new mapping tool for supervised and unsupervised analysis of multivariate binary data with multiple items, questions, or response variables. The mapping assumes an underlying proximity response function, where participants can have multiple… read more here.
Keywords: supervised unsupervised; new mapping; proximity; item ... See more keywords
Discovery of key molecular signatures for diagnosis and therapies of glioblastoma by combining supervised and unsupervised learning approaches
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-79391-2
Abstract: Glioblastoma (GBM) is the most malignant brain cancer and one of the leading causes of cancer-related death globally. So, identifying potential molecular signatures and associated drug molecules are crucial for diagnosis and therapies of GBM.… read more here.
Keywords: supervised unsupervised; combining supervised; gbm; unsupervised learning ... See more keywords
Do Longitudinal Trends in Tobacco 21-Related Media Coverage Correlate with Policy Support? an Exploratory Analysis Using Supervised and Unsupervised Machine Learning Methods.
Sign Up to like & getrecommendations! Published in 2020 at "Health communication"
DOI: 10.1080/10410236.2020.1816282
Abstract: Media coverage can impact support for health policies and, ultimately, compliance with those policies. Prior research found consistent, high support for Tobacco 21 policies, which raise the minimum legal age of tobacco purchase to 21,… read more here.
Keywords: tobacco; media coverage; analysis; support ... See more keywords
SUPERVISED AND UNSUPERVISED LEARNING TO DEFINE THE CARDIOVASCULAR RISK OF PATIENTS ACCORDING TO AN EXTRACELLULAR VESICLE MOLECULAR SIGNATURE.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of hypertension"
DOI: 10.1097/01.hjh.0000836712.81943.92
Abstract: OBJECTIVE Secreted extracellular vesicles (EVs) are membrane-bound nanoparticles released from cells. Since their content reflect the specific signatures of cellular activation and injury, EVs display a strong potential as biomarkers in the cardiovascular (CV) field.… read more here.
Keywords: signature; risk; patients according; supervised unsupervised ... See more keywords
ESW Edge Weights: Ensemble Stochastic Watershed Edge Weights for Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3173793
Abstract: Hyperspectral image (HSI) classification is a topic of active research. One of the main challenges of HSI classification is the lack of reliable labeled samples. Various semi-supervised and unsupervised classification methods are proposed to handle… read more here.
Keywords: classification; semi supervised; edge weights; supervised unsupervised ... See more keywords
Combining Supervised and Unsupervised Learning for Improved miRNA Target Prediction
Sign Up to like & getrecommendations! Published in 2018 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2017.2727042
Abstract: MicroRNAs (miRNAs) are short non-coding RNAs which bind to mRNAs and regulate their expression. MiRNAs have been found to be associated with initiation and progression of many complex diseases. Investigating miRNAs and their targets can… read more here.
Keywords: improved mirna; unsupervised learning; combining supervised; learning improved ... See more keywords