From Classic to Cutting-Edge: A Near-Perfect Global Thresholding Approach with Machine Learning.
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| Title: | From Classic to Cutting-Edge: A Near-Perfect Global Thresholding Approach with Machine Learning. |
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| Authors: | Tarbă, Nicolae1, nicolae.tarba@upb.ro, Boiangiu, Costin-Anton1, Voncilă, Mihai-Lucian1 |
| Source: | Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 14, p8096, 19p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 186928666 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/app15148096 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 8096 Titles: – TitleFull: From Classic to Cutting-Edge: A Near-Perfect Global Thresholding Approach with Machine Learning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tarbă, Nicolae – PersonEntity: Name: NameFull: Boiangiu, Costin-Anton – PersonEntity: Name: NameFull: Voncilă, Mihai-Lucian IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 07 Text: Jul2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 20763417 Numbering: – Type: volume Value: 15 – Type: issue Value: 14 Titles: – TitleFull: Applied Sciences (2076-3417) Type: main |
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