Results 21 to 30 of about 356,686 (298)
Unsupervised Learning of Morphology [PDF]
Computational Linguistics, 2011 This article surveys work on Unsupervised Learning of Morphology. We define Unsupervised Learning of Morphology as the problem of inducing a description (of some kind, even if only morpheme-segmentation) of how orthographic words are built up given only raw text data of a language.
Hammarström, H. ; https://orcid.org/0000-0003-0120-6396 +1 more
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Unsupervised Change Detection Using Ground-based Radar Image
Leida xuebao, 2020 Ground-based radar is a microwave remote sensing imaging technology that has been gradually developed throughout the past 20 years so that it has become mature. At present, it has been widely used in monitoring geological disasters such as landslides and
HUANG Pingping +5 more
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Unsupervised learning and generalization [PDF]
Proceedings of International Conference on Neural Networks (ICNN'96), 2002 The concept of generalization is defined for a general class of unsupervised learning machines. The generalization error is a straightforward extension of the corresponding concept for supervised learning, and may be estimated empirically using a test set or by statistical means-in close analogy with supervised learning.
Lars Kai Hansen, Jan Larsen
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Supervised pansharpening methods require the ground truth, which is generally unavailable. Therefore, the popularity of unsupervised pansharpening methods has increased.
Wenxiu Diao +3 more
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CoRR, 2018 Contrast and quality of ultrasound images are adversely affected by the excessive presence of speckle. However, being an inherent imaging property, speckle helps in tissue characterization and tracking. Thus, despeckling of the ultrasound images requires the reduction of speckle extent without any oversmoothing.
Deepak Mishra 0003 +3 more
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, 2012 In this paper we present a new model of semantic features that, unlike previously presented methods, does not rely on the presence of a labeled training data base, as the creation of the feature extraction function is done in an unsupervised manner.
Claudio Cusano +2 more
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ClassCut for Unsupervised Class Segmentation [PDF]
, 2010 We propose a novel method for unsupervised class segmentation on a set of images. It alternates between segmenting object instances and learning a class model.
Bogdan Alexe +5 more
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Frontiers in Microbiology, 2021 The advent of next-generation sequencing technologies allowed relative quantification of microbiome communities and their spatial and temporal variation.
Elies Ramon +6 more
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CoRR, 2019 26 pages, added comparison with standard quantification ...
Albert Ziegler 0001, Pawel Czyz
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vfonsecad/unsupervised-sample-selection: publication
, 2021 This repository is maintained at https://github.com/vfonsecad/unsupervised-sample ...
Bart De Ketelaere +3 more
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