Statistical compressive sensing method for Hadamard-based single-pixel microscopy supported by kernel density estimators Article Swipe
H. Tobon-Maya
,
S. I. Zapata-Valencia
,
M. Obando
,
F. Lucka
,
E. Tajahuerce
,
J. Lancis
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3788/ai.2025.10001
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3788/ai.2025.10001
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3788/ai.2025.10001
- https://www.researching.cn/ArticlePdf/m00132/2026/3/1/A00002.pdf
- OA Status
- hybrid
- References
- 25
- OpenAlex ID
- https://openalex.org/W7114912418
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W7114912418Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3788/ai.2025.10001Digital Object Identifier
- Title
-
Statistical compressive sensing method for Hadamard-based single-pixel microscopy supported by kernel density estimatorsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
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2025-12-12Full publication date if available
- Authors
-
H. Tobon-Maya, S. I. Zapata-Valencia, M. Obando, F. Lucka, E. Tajahuerce, J. LancisList of authors in order
- Landing page
-
https://doi.org/10.3788/ai.2025.10001Publisher landing page
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https://www.researching.cn/ArticlePdf/m00132/2026/3/1/A00002.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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hybridOpen access status per OpenAlex
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https://www.researching.cn/ArticlePdf/m00132/2026/3/1/A00002.pdfDirect OA link when available
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Kernel density estimation, Compressed sensing, Estimator, Kernel (algebra), Algorithm, Mathematics, Computer science, Artificial intelligence, Pattern recognition (psychology), Computer vision, Noise (video), Microscopy, Materials science, Sample (material), Statistical analysis, Probability density functionTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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25Number of works referenced by this work
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