Results 41 to 50 of about 134,390 (294)
Multi-view subspace clustering for face images [PDF]
© 2015 IEEE. In many real-world computer vision applications, such as multi-camera surveillance, the objects of interest are captured by visual sensors concurrently, resulting in multi-view data.
X Zhang (6084905) +4 more
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A Feature-Reduction Multi-View k-Means Clustering Algorithm
The k-means clustering algorithm is the oldest and most known method in cluster analysis. It has been widely studied with various extensions and applied in a variety of substantive areas.
Miin-Shen Yang, Kristina P. Sinaga
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Kernel-Induced Incomplete Multi-view Clustering
With the development of technology, data often have multiple forms which come from multiple sources. The multi-view clustering algorithm aims to use the complementary information existing in different sources for clustering.
ZHANG Wei, DENG Zhaohong, WANG Shitong
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Self-correction of 3D reconstruction from multi-view stereo images [PDF]
We present a self-correction approach to improving the 3D reconstruction of a multi-view 3D photogrammetry system. The self-correction approach has been able to repair the reconstructed 3D surface damaged by depth discontinuities.
Ju, X +11 more
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Diversity-induced Multi-view Subspace Clustering Algorithm with Grouping Effect [PDF]
The multi-view subspace clustering algorithm, a type of multi-view clustering algorithm, emphasizes discovering potential subspaces in multi-view data and clustering based on these subspaces.
ZHANG Yuechen, GE Hongwei, LI Ting
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When processing a multi-view, epilepsy electroencephalogram (EEG) dataset, the traditional single-view clustering algorithms cannot fully mine the correlation information between each view and identify the importance of each view because of the ...
Jiaqi Zhu +7 more
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Incomplete Multi-view Clustering via Cross-view Relation Transfer [PDF]
In this paper, we consider the problem of multi-view clustering on incomplete views. Compared with complete multi-view clustering, the view-missing problem increases the difficulty of learning common representations from different views.
Chang, Dongxia +3 more
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Multi-view clustering via consensus coefficient matrix and separate segmentation matrices
In recent years, achieving data from different sources and different views has caused to have many multi-view data sets. Among multi-view learning methods, multi-view clustering has been considered as an appropriate method to analyse these data by many ...
Fatemeh Sadjadi +2 more
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Robust Self-Weighted Multi-View Projection Clustering [PDF]
Many real-world applications involve data collected from different views and with high data dimensionality. Furthermore, multi-view data always has unavoidable noise.
Wang, Xuanhong +5 more
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Generative Partial Multi-View Clustering
This paper is an extension to our previous work: "Wang Q, Ding Z, Tao Z, et al. Partial multi-view clustering via consistent GAN[C]//2018 IEEE International Conference on Data Mining (ICDM). IEEE, 2018: 1290-1295."
Qianqian Wang 0001 +4 more
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