Semi-supervised learning using multiple one-dimensional embedding based adaptive interpolation

DOI10.1142/S0219691316400026zbMath1333.68236OpenAlexW2236497445MaRDI QIDQ2801846

Jian-zhong Wang

Publication date: 22 April 2016

Published in: International Journal of Wavelets, Multiresolution and Information Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0219691316400026

zbMATH Keywords

interpolationsemi-supervised learning1D multi-embeddingmultiple 1D embedding

Mathematics Subject Classification ID

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

Related Items (8)

Wavelet-based extended morphological profile and deep autoencoder for hyperspectral image classification ⋮ The performance of semi-supervised Laplacian regularized regression with the least square loss ⋮ Semi-supervised learning using autodidactic interpolation on sparse representation-based multiple one-dimensional embedding ⋮ Hyperspectral image classification using wavelet transform-based smooth ordering ⋮ Semi-supervised learning using ensembles of multiple 1D-embedding-based label boosting ⋮ Multiple one-dimensional embedding clustering scheme for hyperspectral image classification ⋮ A novel semi-supervised learning framework for hyperspectral image classification ⋮ 1D embedding multi-category classification methods

Uses Software

• SGTlight

Cites Work

• Principal component analysis.
• Diffusion maps
• Harmonic Analysis of Digital Data Bases
• Generalized Tree-Based Wavelet Transform
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