Matrix exponential based semi-supervised discriminant embedding for image classification

DOI10.1016/j.patcog.2016.07.029zbMath1428.68235OpenAlexW2481635351WikidataQ115568076 ScholiaQ115568076MaRDI QIDQ2289594

Y. El Traboulsi, F. Dornaika

Publication date: 23 January 2020

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2016.07.029

zbMATH Keywords

feature extractionimage classificationmatrix exponentialgraph-based semi-supervised learningdistance diffusion mappingsemi-supervised discriminant embedding (SDE)small-sample-size (SSS) problem

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Related Items (5)

Matrix exponential based discriminant locality preserving projections for feature extraction ⋮ On general matrix exponential discriminant analysis methods for high dimensionality reduction ⋮ Flexible semi-supervised embedding based on adaptive loss regression: application to image categorization ⋮ A novel discriminant locality preserving projections method ⋮ Semi-supervised classification via simultaneous label and discriminant embedding estimation

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• Nineteen Dubious Ways to Compute the Exponential of a Matrix
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Flexible Manifold Embedding: A Framework for Semi-Supervised and Unsupervised Dimension Reduction

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