Target Recognition Based on Singular Value Decomposition in a Single-Pixel Non-Imaging System Article Swipe
Lin-Shan Chen
,
Yining Zhao
,
Cheng Ren
,
Chong Wang
,
De-Zhong Cao
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/photonics11100909
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/photonics11100909
We propose a single-pixel non-imaging target recognition scheme which that exploits the singular values of target objects. By choosing the first few singular values and the corresponding unitary matrices in the singular value decomposition of all the targets, we form the measurement matrices to be projected onto the target in a single-pixel non-imaging scheme. One can quickly and accurately recognize the target images after directly recording the single-pixel signals. From the simulation and experimental results, we found that the accuracy of target recognition was high when the first three singular values were used. The efficiency of target recognition was improved by randomly rearranging the orders of the row vectors in the measurement matrix. Therefore, our research results offer a novel perspective for recognizing non-imaging targets.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/photonics11100909
- OA Status
- gold
- Cited By
- 2
- References
- 36
- Related Works
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- OpenAlex ID
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All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4402923483Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/photonics11100909Digital Object Identifier
- Title
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Target Recognition Based on Singular Value Decomposition in a Single-Pixel Non-Imaging SystemWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-27Full publication date if available
- Authors
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Lin-Shan Chen, Yining Zhao, Cheng Ren, Chong Wang, De-Zhong CaoList of authors in order
- Landing page
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https://doi.org/10.3390/photonics11100909Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.3390/photonics11100909Direct OA link when available
- Concepts
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Pixel, Singular value decomposition, Computer science, Computer vision, Artificial intelligence, Decomposition, Optics, Pattern recognition (psychology), Physics, Biology, EcologyTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
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36Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.the | 11, 19, 25, 30, 36, 40, 47, 60, 66, 70, 78, 86, 103, 106, 110 |
| abstract_inverted_index.was | 83, 98 |
| abstract_inverted_index.From | 69 |
| abstract_inverted_index.form | 39 |
| abstract_inverted_index.high | 84 |
| abstract_inverted_index.onto | 46 |
| abstract_inverted_index.that | 9, 77 |
| abstract_inverted_index.were | 91 |
| abstract_inverted_index.when | 85 |
| abstract_inverted_index.after | 63 |
| abstract_inverted_index.first | 20, 87 |
| abstract_inverted_index.found | 76 |
| abstract_inverted_index.novel | 119 |
| abstract_inverted_index.offer | 117 |
| abstract_inverted_index.three | 88 |
| abstract_inverted_index.used. | 92 |
| abstract_inverted_index.value | 32 |
| abstract_inverted_index.which | 8 |
| abstract_inverted_index.images | 62 |
| abstract_inverted_index.orders | 104 |
| abstract_inverted_index.scheme | 7 |
| abstract_inverted_index.target | 5, 15, 48, 61, 81, 96 |
| abstract_inverted_index.values | 13, 23, 90 |
| abstract_inverted_index.matrix. | 112 |
| abstract_inverted_index.propose | 1 |
| abstract_inverted_index.quickly | 56 |
| abstract_inverted_index.results | 116 |
| abstract_inverted_index.scheme. | 53 |
| abstract_inverted_index.unitary | 27 |
| abstract_inverted_index.vectors | 108 |
| abstract_inverted_index.accuracy | 79 |
| abstract_inverted_index.choosing | 18 |
| abstract_inverted_index.directly | 64 |
| abstract_inverted_index.exploits | 10 |
| abstract_inverted_index.improved | 99 |
| abstract_inverted_index.matrices | 28, 42 |
| abstract_inverted_index.objects. | 16 |
| abstract_inverted_index.randomly | 101 |
| abstract_inverted_index.research | 115 |
| abstract_inverted_index.results, | 74 |
| abstract_inverted_index.signals. | 68 |
| abstract_inverted_index.singular | 12, 22, 31, 89 |
| abstract_inverted_index.targets, | 37 |
| abstract_inverted_index.targets. | 124 |
| abstract_inverted_index.projected | 45 |
| abstract_inverted_index.recognize | 59 |
| abstract_inverted_index.recording | 65 |
| abstract_inverted_index.Therefore, | 113 |
| abstract_inverted_index.accurately | 58 |
| abstract_inverted_index.efficiency | 94 |
| abstract_inverted_index.simulation | 71 |
| abstract_inverted_index.measurement | 41, 111 |
| abstract_inverted_index.non-imaging | 4, 52, 123 |
| abstract_inverted_index.perspective | 120 |
| abstract_inverted_index.rearranging | 102 |
| abstract_inverted_index.recognition | 6, 82, 97 |
| abstract_inverted_index.recognizing | 122 |
| abstract_inverted_index.experimental | 73 |
| abstract_inverted_index.single-pixel | 3, 51, 67 |
| abstract_inverted_index.corresponding | 26 |
| abstract_inverted_index.decomposition | 33 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.66018597 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |