Results 41 to 50 of about 6,372,670 (283)
Unsupervised Relation Extraction for E-Learning Applications [PDF]
, 2011 A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of PhilosophyIn this modern era many educational institutes and business organisations are adopting the e-Learning approach as it ...
Afzal, Naveed
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A Single-Stage Unsupervised Denoising Low-Illumination Enhancement Network Based on Swin-Transformer
IEEE Access, 2023 Traditional low-light enhancement methods are often based on paired datasets for training. The training data is difficult to obtain and the resulting model has poor generalization.
Qian Zhang +3 more
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SUN: Stochastic UNsupervised Learning for Data Noise and Uncertainty Reduction
Applied SciencesUnsupervised learning methods significantly benefit various practical applications by effectively identifying intrinsic patterns within unlabelled data.
Nicholas Christakis, Dimitris Drikakis
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Unsupervised spectral learning
CoRR, 2012 In spectral clustering and spectral image segmentation, the data is partioned starting from a given matrix of pairwise similarities S. the matrix S is constructed by hand, or learned on a separate training set. In this paper we show how to achieve spectral clustering in unsupervised mode.
Susan M. Shortreed, Marina Meila
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Unsupervised Learning of Visual Structure [PDF]
Journal of Vision, 2002 To learn a visual code in an unsupervised manner, one may attempt to capture those features of the stimulus set that would contribute significantly to a statistically efficient representation (as dictated, e.g., by the Minimum Description Length principle).
Shimon Edelman +2 more
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Jurnal Riset Akuntansi dan Bisnis Airlangga, 2023 This research aims to assess the usage of unsupervised learning in detecting financial fraud across various financial industries by identifying cognitive constructs, benefits, economic optimization, and challenges associated with fraud detection ...
Nadia Husnaningtyas, Totok Dewayanto
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Classification of Medical Images Based on Unsupervised Algorithms: A Review
International Journal of Research and Applied TechnologyArtificial intelligence models are becoming increasingly essential in biomedical research and healthcare services. Various healthcare organizations utilize information-based machine learning and image-processing methods for the diagnosis of diseases ...
Imad Majed Zeebaree +1 more
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Self-Supervised and Few-Shot Contrastive Learning Frameworks for Text Clustering
IEEE Access, 2023 Contrastive learning is a promising approach to unsupervised learning, as it inherits the advantages of well-studied deep models without a dedicated and complex model design. In this paper, based on bidirectional encoder representations from transformers
Haoxiang Shi, Tetsuya Sakai
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UniverseThis review investigates the application of unsupervised machine learning algorithms to astronomical data. Unsupervised machine learning enables researchers to analyze large, high-dimensional, and unlabeled datasets and is sometimes considered more ...
Chih-Ting Kuo, Duo Xu, Rachel Friesen
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Nuclear Engineering and Technology, 2022 This paper proposes an algorithm for signal validation using unsupervised methods in emergency situations at nuclear power plants (NPPs) when signals are rapidly changing.
Younhee Choi +2 more
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