Results 51 to 60 of about 38,536 (261)
HSSDA: Hierarchical relation aided Semi-Supervised Domain Adaptation
AI Open, 2022 The mainstream domain adaptation (DA) methods transfer the supervised source domain knowledge to the unsupervised or semi-supervised target domain, so as to assist the classification task in the target domain.
Xiechao Guo, Ruiping Liu, Dandan Song
doaj +1 more source
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Journal of Big DataSemi-supervised classification demonstrates effective performance in categorizing short-length texts, such as social media posts and online reviews, through the utilization of limited labeled data.
Mingqiang Wu
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Optimistic semi-supervised least squares classification [PDF]
2016 23rd International Conference on Pattern Recognition (ICPR), 2016 6 pages, 6 figures.
Krijthe, Jesse H., Loog, Marco
openaire +3 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Treatment of disorders of consciousness (DoC) remains a major clinical challenge, and noninvasive, targeted modulation of deep brain structures has emerged as a promising therapeutic strategy. We aimed to evaluate the feasibility/safety and preliminary effects of thalamic temporal interference stimulation (TIS) targeting centromedian‐
Gengyao Hu +7 more
wiley +1 more source
A Comparison of Semi-Supervised Classification Approaches for Software Defect Prediction
Journal of Intelligent Systems, 2014 Predicting the defect-prone modules when the previous defect labels of modules are limited is a challenging problem encountered in the software industry. Supervised classification approaches cannot build high-performance prediction models with few defect
Catal Cagatay
doaj +1 more source
An Auto-Adjustable Semi-Supervised Self-Training Algorithm
Algorithms, 2018 Semi-supervised learning algorithms have become a topic of significant research as an alternative to traditional classification methods which exhibit remarkable performance over labeled data but lack the ability to be applied on large amounts of ...
Ioannis E. Livieris +3 more
doaj +1 more source
Swarm Intelligence in Semi-supervised Classification
CoRR, 2017 This Paper represents a literature review of Swarm intelligence algorithm in the area of semi-supervised classification. There are many research papers for applying swarm intelligence algorithms in the area of machine learning. Some algorithms of SI are applied in the area of ML either solely or hybrid with other ML algorithms.
Shahira Shaaban Azab, Hesham Ahmed Hefny
openaire +2 more sources
Semi-supervised Collaborative Text Classification [PDF]
, 2007 Most text categorization methods require text content of documents that is often difficult to obtain. We consider "Collaborative Text Categorization", where each document is represented by the feedback from a large number of users. Our study focuses on the semi-supervised case in which one key challenge is that a significant number of users have not ...
Rong Jin 0001, Ming Wu, Rahul Sukthankar
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A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Advanced Engineering Materials, EarlyView.Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source