Approximate spectral clustering density-based similarity for noisy datasets

Mashaan Alshammari; Masahiro Takatsuka

doi:10.1016/j.patrec.2019.08.020

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Approximate spectral clustering density-based similarity for noisy datasets

Mashaan Alshammari Masahiro Takatsuka

Year: 2019 Journal: Pattern Recognition Letters Vol: 128 Pages: 155-161 Publisher: Elsevier BV

DOI: 10.1016/j.patrec.2019.08.020

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Keywords:

Spectral clustering Cluster analysis Preprocessor Similarity (geometry) Pattern recognition (psychology) Vector quantization Computer science Mathematics Similarity measure Graph Artificial intelligence Combinatorics Algorithm

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Remote-Sensing Image Classification

Physical Sciences → Engineering → Media Technology

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Clustering Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Approximate spectral clustering density-based similarity for noisy datasets

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