Results 41 to 50 of about 3,746,359 (297)
Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences. [PDF]
Nat Commun, 2019 Biomedical repositories such as the UK Biobank provide increasing access to prospectively collected cardiac imaging, however these data are unlabeled, which creates barriers to their use in supervised machine learning. We develop a weakly supervised deep
Fries JA +13 more
europepmc +2 more sources
Semi-Supervised Hierarchical Graph Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 Node classification and graph classification are two graph learning problems that predict the class label of a node and the class label of a graph respectively. A node of a graph usually represents a real-world entity, e.g., a user in a social network, or a document in a document citation network.
Jia Li +3 more
openaire +4 more sources
Remote Sensing, 2021 The size of the training data set is a major determinant of classification accuracy. Nevertheless, the collection of a large training data set for supervised classifiers can be a challenge, especially for studies covering a large area, which may be ...
Christopher A. Ramezan +3 more
semanticscholar +1 more source
Generative Supervised Classification Using Dirichlet Process Priors. [PDF]
, 2010 Choosing the appropriate parameter prior distributions associated to a given Bayesian model is a challenging problem. Conjugate priors can be selected for simplicity motivations.
Davy, Manuel, Tourneret, Jean-Yves
core +2 more sources
A Weakly-Supervised Framework for COVID-19 Classification and Lesion Localization From Chest CT
IEEE Transactions on Medical Imaging, 2020 Accurate and rapid diagnosis of COVID-19 suspected cases plays a crucial role in timely quarantine and medical treatment. Developing a deep learning-based model for automatic COVID-19 diagnosis on chest CT is helpful to counter the outbreak of SARS-CoV-2.
Xinggang Wang +7 more
semanticscholar +1 more source
Weakly supervised classification in high energy physics
Journal of High Energy Physics, 2017 As machine learning algorithms become increasingly sophisticated to exploit subtle features of the data, they often become more dependent on simulations.
Lucio Mwinmaarong Dery +3 more
doaj +1 more source
Self-Supervised Learning for Solar Radio Spectrum Classification
Universe, 2022 Solar radio observation is an important way to study the Sun. Solar radio bursts contain important information about solar activity. Therefore, real-time automatic detection and classification of solar radio bursts are of great value for subsequent solar
Siqi Li +4 more
doaj +1 more source
Remote Sensing, 2022 Deep learning methods have become an integral part of computer vision and machine learning research by providing significant improvement performed in many tasks such as classification, regression, and detection. These gains have been also observed in the
Paul Berg, Minh-Tan Pham, Nicolas Courty
doaj +1 more source
Supervised Classification: Quite a Brief Overview
, 2017 The original problem of supervised classification considers the task of automatically assigning objects to their respective classes on the basis of numerical measurements derived from these objects.
Aizerman +125 more
core +1 more source
Economic event detection in company-specific news text [PDF]
, 2018 This paper presents a dataset and supervised classification approach for economic event detection in English news articles. Currently, the economic domain is lacking resources and methods for data-driven supervised event detection.
Hoste, Veronique +2 more
core +1 more source