Results 31 to 40 of about 8,398,730 (304)
Full body virtual try‐on with semi‐self‐supervised learning
Electronics Letters, 2021 This paper proposes a full body virtual try‐on which handles both top and bottom garments and generates realistic try‐on images. For the full body virtual try‐on, this paper addresses lack of suitable training data to align and fit top and bottom ...
Hyug‐Jae Lee +5 more
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Towards semi-supervised ensemble clustering using a new membership similarity measure
Automatika, 2023 Hierarchical clustering is a common type of clustering in which the dataset is hierarchically divided and represented by a dendrogram. Agglomerative Hierarchical Clustering (AHC) is a common type of hierarchical clustering in which clusters are created ...
Wenjun Li, Ting Li, Musa Mojarad
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Graph Laplacian for Semi-supervised Learning
, 2023 Semi-supervised learning is highly useful in common scenarios where labeled data is scarce but unlabeled data is abundant. The graph (or nonlocal) Laplacian is a fundamental smoothing operator for solving various learning tasks. For unsupervised clustering, a spectral embedding is often used, based on graph-Laplacian eigenvectors.
Streicher, Or, Gilboa, Guy
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Driving Maneuver Classification Using Domain Specific Knowledge and Transfer Learning
IEEE Access, 2021 With the increasing number of vehicles, the usage of technology has also been increased in the transportation system. Although automobile companies are using advanced technologies to develop high performing transports, traffic safety still remains to be ...
Supriya Sarker +2 more
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Semi-supervised Vocabulary-Informed Learning [PDF]
2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016 Despite significant progress in object categorization, in recent years, a number of important challenges remain, mainly, ability to learn from limited labeled data and ability to recognize object classes within large, potentially open, set of labels. Zero-shot learning is one way of addressing these challenges, but it has only been shown to work with ...
Yanwei Fu 0001, Leonid Sigal
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Efficiently Learning the Graph for Semi-supervised Learning
CoRR, 2023 29 pages, 9 ...
Dravyansh Sharma, Maxwell Jones
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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
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Semi-Supervised Learning with Scarce Annotations [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020 Workshop on Deep Vision, CVPR ...
Rebuffi, S-A +4 more
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Lithofacies Classification Using Supervised and Semi-Supervised Machine Learning Approach [PDF]
, 2021 The machine learning approach can help Geoscientists do their work in well log analysis to developing the oil and gas field. Prediction categorical or numerical response variable using a set of predictor variables supervises and semi-supervises learning ...
Hardanto, Lilik T.; Department of Computer Science, Binus University, Jakarta, 11530, Indonesia +3 more
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AlgorithmsPredicting the energy consumption of buildings plays a critical role in supporting utility providers, users, and facility managers in minimizing energy waste and optimizing operational efficiency. However, this prediction becomes difficult because of the
Sami Kabir +2 more
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