Extraction of Visual Communication Design Elements Based on Machine Learning.
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| Title: | Extraction of Visual Communication Design Elements Based on Machine Learning. |
|---|---|
| Authors: | Lin Liu1 liulin19910600@163.com |
| Source: | Computer-Aided Design & Applications. 2025 Special Issue, Vol. 22, p181-194. 14p. |
| Subjects: | Machine learning, Automatic classification, Visual communication, Classification algorithms, Algorithms |
| Abstract: | As visual communication design (VCD) rapidly evolves, traditional methods for extracting design elements struggle to meet the demands for efficiency and accuracy. This article deeply explores the application achievements of machine learning in the intelligent extraction of elements in educational applications. Based on this method, an algorithm for automatically extracting classifications from a comprehensive dataset was studied and constructed. In the design and classification process of intelligent application machine learning, the potential educational applications of the algorithm for automatic classification were deeply explored. In this teaching application, design elements can effectively conduct precision case study exercises in systematic practical learning cases. [ABSTRACT FROM AUTHOR] |
| Copyright of Computer-Aided Design & Applications is the property of Computer-Aided Design & Applications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 186758318 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Extraction of Visual Communication Design Elements Based on Machine Learning. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Lin+Liu%22">Lin Liu</searchLink><relatesTo>1</relatesTo><i> liulin19910600@163.com</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Computer-Aided+Design+%26+Applications%22">Computer-Aided Design & Applications</searchLink>. 2025 Special Issue, Vol. 22, p181-194. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Automatic+classification%22">Automatic classification</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+communication%22">Visual communication</searchLink><br /><searchLink fieldCode="DE" term="%22Classification+algorithms%22">Classification algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: As visual communication design (VCD) rapidly evolves, traditional methods for extracting design elements struggle to meet the demands for efficiency and accuracy. This article deeply explores the application achievements of machine learning in the intelligent extraction of elements in educational applications. Based on this method, an algorithm for automatically extracting classifications from a comprehensive dataset was studied and constructed. In the design and classification process of intelligent application machine learning, the potential educational applications of the algorithm for automatic classification were deeply explored. In this teaching application, design elements can effectively conduct precision case study exercises in systematic practical learning cases. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Computer-Aided Design & Applications is the property of Computer-Aided Design & Applications and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=186758318 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.14733/cadaps.2025.S4.181-194 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 181 Subjects: – SubjectFull: Machine learning Type: general – SubjectFull: Automatic classification Type: general – SubjectFull: Visual communication Type: general – SubjectFull: Classification algorithms Type: general – SubjectFull: Algorithms Type: general Titles: – TitleFull: Extraction of Visual Communication Design Elements Based on Machine Learning. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Lin Liu IsPartOfRelationships: – BibEntity: Dates: – D: 05 M: 02 Text: 2025 Special Issue Type: published Y: 2025 Identifiers: – Type: issn-print Value: 16864360 Numbering: – Type: volume Value: 22 Titles: – TitleFull: Computer-Aided Design & Applications Type: main |
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