Results 111 to 120 of about 9,565 (204)

Neural Collaborative Subspace Clustering [PDF]

, 2019
We introduce the Neural Collaborative Subspace Clustering, a neural model that discovers clusters of data points drawn from a union of low-dimensional subspaces.
Harandi, Mehrtash, Zhang, Tong, Li, Hongdong, Ji, Pan, Huang, Wenbing   +4 more
core  

Enhanced subspace clustering

, 2012
Subspace clustering overcomes the curse of dimensionality that traditional clustering suffered, by finding groups of objects that are homogeneous in subspaces of the data, instead of the full space.
Sim, Kelvin Sian Hui.
core  

Graph-Constrained Residual Self-Expressive Subspace Clustering Network for Hyperspectral Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral images are widely use due to their rich spectral information. Meanwhile, the difficult acquisition of data labels makes unsupervised classification attracts attention.
Kun Huang, Xin Li, Yingdong Pi, Hao Cheng, Guowei Xu   +4 more
doaj   +1 more source

Markov-Embedded Affinity Learning with Connectivity Constraints for Subspace Clustering

Applied Sciences
Subspace clustering algorithms have demonstrated remarkable success across diverse fields, including object segmentation, gene clustering, and recommendation systems.
Wenjiang Shao, Xiaowei Zhang
doaj   +1 more source

An Adaptive Sparse Subspace Clustering for Cell Type Identification. [PDF]

Front Genet, 2020
Zheng R, Liang Z, Chen X, Tian Y, Cao C, Li M.   +5 more
europepmc   +1 more source

Adaptive Weighted Graph Fusion Incomplete Multi-View Subspace Clustering. [PDF]

Sensors (Basel), 2020
Zhang P, Wang S, Hu J, Cheng Z, Guo X, Zhu E, Cai Z.   +6 more
europepmc   +1 more source

Multimodal MRI Brain Tumor Image Segmentation Using Sparse Subspace Clustering Algorithm. [PDF]

Comput Math Methods Med, 2020
Liu L, Kuang L, Ji Y.
europepmc   +1 more source

Sample Latent Feature-Associated Low-Rank Subspace Clustering for Hyperspectral Band Selection

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
In recent years, subspace clustering has become increasingly popular and achieved great success in band selection (BS) of hyperspectral imagery. However, current subspace clustering approaches are mostly insufficient in capturing the fine spatial ...
Yujie Guo, Xin Zhao, Xudong Sun, Jiahua Zhang, Xiaodi Shang   +4 more
doaj   +1 more source

Soft subspace clustering with competitive agglomeration

, 2011
In this paper, two novel soft subspace clustering algorithms, namely fuzzy weighting subspace clustering with competitive agglomeration (FWSCA) and entropy weighting subspace clustering with competitive agglomeration (EWSCA), are proposed to overcome the
Zhu, L, Cao, L, Yang, J
core   +1 more source

Similarity Measures for Clustering SNP and Epidemiological Data [PDF]

The issue of suitable similarity measures for a joint consideration of so called SNP data and epidemiological variables arises from the GENICA (Interdisciplinary Study Group on Gene Environment Interaction and Breast Cancer in Germany) casecontrol study ...
Selinski, Silvia
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