Results 71 to 80 of about 601,753 (327)
The Peaking Phenomenon in Semi-supervised Learning [PDF]
, 2016 For the supervised least squares classifier, when the number of training objects is smaller than the dimensionality of the data, adding more data to the training set may first increase the error rate before decreasing it. This, possibly counterintuitive, phenomenon is known as peaking. In this work, we observe that a similar but more pronounced version
Jesse H. Krijthe +3 more
openaire +4 more sources
AIFor automatic tumor segmentation in magnetic resonance imaging (MRI), deep learning offers very powerful technical support with significant results. However, the success of supervised learning is strongly dependent on the quantity and accuracy of labeled
Chengcheng Jin +2 more
doaj +1 more source
On Ensemble SSL Algorithms for Credit Scoring Problem
Informatics, 2018 Credit scoring is generally recognized as one of the most significant operational research techniques used in banking and finance, aiming to identify whether a credit consumer belongs to either a legitimate or a suspicious customer group.
Ioannis E. Livieris +4 more
doaj +1 more source
AI-Assisted Cotton Grading: Active and Semi-Supervised Learning to Reduce the Image-Labelling Burden
Sensors, 2023 The assessment of food and industrial crops during harvesting is important to determine the quality and downstream processing requirements, which in turn affect their market value. While machine learning models have been developed for this purpose, their
Oliver J. Fisher +4 more
doaj +1 more source
Semi-Supervised Radio Signal Identification
, 2017 Radio emitter recognition in dense multi-user environments is an important tool for optimizing spectrum utilization, identifying and minimizing interference, and enforcing spectrum policy.
chapelle +9 more
core +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To identify metabolic patterns in the brain and musculoskeletal system of stiff person syndrome spectrum disorders (SPSD) patients over time using PET imaging and evaluate the impact of immune therapy on metabolic activity as a surrogate for treatment response.
Munther M. Queisi +4 more
wiley +1 more source
Dual Learning-Based Safe Semi-Supervised Learning
IEEE Access, 2018 In many real-world applications, labeled instances are generally limited and expensively collected, while the most instances are unlabeled and the amount is often sufficient.
Haitao Gan +3 more
doaj +1 more source
A semi-supervised spam mail detector [PDF]
, 2006 This document describes a novel semi-supervised approach to spam classification, which was successful at the ECML/PKDD 2006 spam classification challenge.
Pfahringer, Bernhard
core +2 more sources
Semi-Supervised Learning for Neural Machine Translation
, 2016 While end-to-end neural machine translation (NMT) has made remarkable progress recently, NMT systems only rely on parallel corpora for parameter estimation. Since parallel corpora are usually limited in quantity, quality, and coverage, especially for low-
Cheng, Yong +6 more
core +1 more source
Arthritis Care &Research, Accepted Article.Objectives This study aims to develop hip morphology‐based radiographic hip osteoarthritis (RHOA) risk prediction models and investigates the added predictive value of hip morphology measurements and the generalizability to different populations. Methods We combined data from nine prospective cohort studies participating in the World COACH consortium ...
Myrthe A. van den Berg +26 more
wiley +1 more source