Unsupervised Feature Selection via a Dual-Graph Autoencoder with <inline-formula><math display="inline"><semantics><mrow><msub><mi mathvariant="bold-script">l</mi><mrow><mn mathvariant="bold">2</mn><mo mathvariant="bold">,</mo><mn mathvariant="bold">1</mn><mo mathvariant="bold">/</mo><mn mathvariant="bold">2</mn></mrow></msub></mrow></semantics></math></inline-formula>-Norm for [<sup>68</sup>Ga]Ga-Pentixafor PET Imaging of Glioma
In the era of big data, high-dimensional datasets have become increasingly common in fields such as biometrics, computer vision, and medical imaging. While such data contain abundant information, they are often accompanied by substantial noise, high redundancy, and complex intrinsic structures, posi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/11/6177 |
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