GJTD-LR: A Trainable Grouped Joint Tensor Dictionary With Low-Rank Prior for Single Hyperspectral Image Super-Resolution

Research article (IEEE Transactions on Geoscience and Remote Sensing, 2022) · cited 17× · AI/ML
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GJTD-LR: A Trainable Grouped Joint Tensor Dictionary With Low-Rank Prior for Single Hyperspectral Image Super-Resolution

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GJTD-LR: A Trainable Grouped Joint Tensor Dictionary With Low-Rank Prior for Single Hyperspectral Image Super-Resolution is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). GJTD-LR: A Trainable Grouped Joint Tensor Dictionary With Low-Rank Prior for Single Hyperspectral Image Super-Resolution. Retrieved May 24, 2026, from https://4ort.xyz/entity/gjtd-lr-a-trainable-grouped-joint-tensor-dictionary-with-low-rank-prior-for-single-hyperspectral-image-super-resolution
MLA “GJTD-LR: A Trainable Grouped Joint Tensor Dictionary With Low-Rank Prior for Single Hyperspectral Image Super-Resolution.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/gjtd-lr-a-trainable-grouped-joint-tensor-dictionary-with-low-rank-prior-for-single-hyperspectral-image-super-resolution.
BibTeX @misc{4ortxyz_gjtd-lr-a-trainable-grouped-joint-tensor-dictionary-with-low-rank-prior-for-single-hyperspectral-image-super-resolution_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{GJTD-LR: A Trainable Grouped Joint Tensor Dictionary With Low-Rank Prior for Single Hyperspectral Image Super-Resolution}}, year = {2026}, url = {https://4ort.xyz/entity/gjtd-lr-a-trainable-grouped-joint-tensor-dictionary-with-low-rank-prior-for-single-hyperspectral-image-super-resolution}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): GJTD-LR: A Trainable Grouped Joint Tensor Dictionary With Low-Rank Prior for Single Hyperspectral Image Super-Resolution — https://4ort.xyz/entity/gjtd-lr-a-trainable-grouped-joint-tensor-dictionary-with-low-rank-prior-for-single-hyperspectral-image-super-resolution (retrieved 2026-05-24)

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