Fusion of Graph Embedding and Sparse Representation for Feature Extraction and Classification of Hyperspectral Imagery

Research article (Photogrammetric Engineering & Remote Sensing, 2017) · cited 17× · AI/ML
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Fusion of Graph Embedding and Sparse Representation for Feature Extraction and Classification of Hyperspectral Imagery

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Fusion of Graph Embedding and Sparse Representation for Feature Extraction and Classification of Hyperspectral Imagery is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Fusion of Graph Embedding and Sparse Representation for Feature Extraction and Classification of Hyperspectral Imagery. Retrieved May 24, 2026, from https://4ort.xyz/entity/fusion-of-graph-embedding-and-sparse-representation-for-feature-extraction-and-classification-of-hyperspectral-imagery
MLA “Fusion of Graph Embedding and Sparse Representation for Feature Extraction and Classification of Hyperspectral Imagery.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/fusion-of-graph-embedding-and-sparse-representation-for-feature-extraction-and-classification-of-hyperspectral-imagery.
BibTeX @misc{4ortxyz_fusion-of-graph-embedding-and-sparse-representation-for-feature-extraction-and-classification-of-hyperspectral-imagery_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Fusion of Graph Embedding and Sparse Representation for Feature Extraction and Classification of Hyperspectral Imagery}}, year = {2026}, url = {https://4ort.xyz/entity/fusion-of-graph-embedding-and-sparse-representation-for-feature-extraction-and-classification-of-hyperspectral-imagery}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Fusion of Graph Embedding and Sparse Representation for Feature Extraction and Classification of Hyperspectral Imagery — https://4ort.xyz/entity/fusion-of-graph-embedding-and-sparse-representation-for-feature-extraction-and-classification-of-hyperspectral-imagery (retrieved 2026-05-24)

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