Image Clustering Using Local Discriminant Models and Global Integration

DOI10.1109/TIP.2010.2049235zbMath1371.94434DBLPjournals/tip/YangXNYZ10WikidataQ44067587 ScholiaQ44067587MaRDI QIDQ5366552

Feiping Nie, Yi Yang, Shuicheng Yan, Dong Xu, Yue-Ting Zhuang

Publication date: 9 October 2017

Published in: IEEE Transactions on Image Processing (Search for Journal in Brave)

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (15)

Locality preserving score for joint feature weights learning ⋮ Thresholded two-phase test sample representation for outlier rejection in biological recognition ⋮ Global discriminative-based nonnegative spectral clustering ⋮ Deep Bayesian unsupervised lifelong learning ⋮ Learning deep discriminative representations with pseudo supervision for image clustering ⋮ Clustering based on local density peaks and graph cut ⋮ Model-free inverse reinforcement learning with multi-intention, unlabeled, and overlapping demonstrations ⋮ Denoising cosine similarity: a theory-driven approach for efficient representation learning ⋮ Achieving deep clustering through the use of variational autoencoders and similarity-based loss ⋮ Refined Spectral Clustering via Embedded Label Propagation ⋮ Unsupervised feature selection based on kernel Fisher discriminant analysis and regression learning ⋮ Adaptive Structure Concept Factorization for Multiview Clustering ⋮ Learning from normalized local and global discriminative information for semi-supervised regression and dimensionality reduction ⋮ Joint sparse principal component analysis ⋮ Learning robust affinity graph representation for multi-view clustering

This page was built for publication: Image Clustering Using Local Discriminant Models and Global Integration