Semisupervised charting for spectral multimodal manifold learning and alignment
作者：
Highlights：
• A novel multimodal data fusion semisupervised manifold learning technic is proposed.
• Functional mapping to extend limited supervised information on modalities manifolds.
• Simultaneously learns manifold in each modality, and aligns them.
• Joint diagonalization of within- and between-modality graph Laplacian.
• Decoupling/modality-specific parts are deemphasized during learning common manifold.
摘要
•A novel multimodal data fusion semisupervised manifold learning technic is proposed.•Functional mapping to extend limited supervised information on modalities manifolds.•Simultaneously learns manifold in each modality, and aligns them.•Joint diagonalization of within- and between-modality graph Laplacian.•Decoupling/modality-specific parts are deemphasized during learning common manifold.
论文关键词：Semi-supervised learning,Multimodal data,Functional map,Manifold learning,Data fusion,Hyperspectral images
论文评审过程：Received 30 April 2020, Revised 17 August 2020, Accepted 6 September 2020, Available online 14 September 2020, Version of Record 25 September 2020.
论文官网地址：https://doi.org/10.1016/j.patcog.2020.107645
