Digital Innovation in Environmental Art Design: The Combination of CAD and Multimodal Fusion Technology.
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| Title: | Digital Innovation in Environmental Art Design: The Combination of CAD and Multimodal Fusion Technology. |
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| Authors: | Mei Bai1 29020@hnzj.edu.cn |
| Source: | Computer-Aided Design & Applications. 2025 Special Issue, Vol. 22, p92-104. 13p. |
| Subjects: | Digital technology, Ecological art, Computer-aided design, Error rates, Feature extraction |
| Abstract: | This article aims to explore digital innovation in environmental art design (EAD), especially the combined use of computer-aided design (CAD) and multimodal fusion technology. To achieve this goal, this study designed and implemented a series of experiments using a high-performance computing environment and rich EAD data sets for model training and feature detection. The results show that the proposed method has high accuracy in environmental art feature detection, with an accuracy rate of 92.5%. Among 1000 test samples, the model correctly extracts the features of 925 samples, with an error rate of only 7.5%. The sample extraction time for feature monitoring results has been reduced by 15 seconds compared to traditional methods. This has greatly improved the efficiency of feature monitoring. In the field of experimental results, the evaluation effect of digital quantitative analysis has an average score of 9.2 in the process of analyzing experimental results, which has a certain efficiency in the multimodal fusion process of method technology. This further proves the digital multimodal technology fusion analysis method. [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: 186716307 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Digital Innovation in Environmental Art Design: The Combination of CAD and Multimodal Fusion Technology. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Mei+Bai%22">Mei Bai</searchLink><relatesTo>1</relatesTo><i> 29020@hnzj.edu.cn</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, p92-104. 13p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Digital+technology%22">Digital technology</searchLink><br /><searchLink fieldCode="DE" term="%22Ecological+art%22">Ecological art</searchLink><br /><searchLink fieldCode="DE" term="%22Computer-aided+design%22">Computer-aided design</searchLink><br /><searchLink fieldCode="DE" term="%22Error+rates%22">Error rates</searchLink><br /><searchLink fieldCode="DE" term="%22Feature+extraction%22">Feature extraction</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This article aims to explore digital innovation in environmental art design (EAD), especially the combined use of computer-aided design (CAD) and multimodal fusion technology. To achieve this goal, this study designed and implemented a series of experiments using a high-performance computing environment and rich EAD data sets for model training and feature detection. The results show that the proposed method has high accuracy in environmental art feature detection, with an accuracy rate of 92.5%. Among 1000 test samples, the model correctly extracts the features of 925 samples, with an error rate of only 7.5%. The sample extraction time for feature monitoring results has been reduced by 15 seconds compared to traditional methods. This has greatly improved the efficiency of feature monitoring. In the field of experimental results, the evaluation effect of digital quantitative analysis has an average score of 9.2 in the process of analyzing experimental results, which has a certain efficiency in the multimodal fusion process of method technology. This further proves the digital multimodal technology fusion analysis method. [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=186716307 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.14733/cadaps.2025.S3.92-104 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 13 StartPage: 92 Subjects: – SubjectFull: Digital technology Type: general – SubjectFull: Ecological art Type: general – SubjectFull: Computer-aided design Type: general – SubjectFull: Error rates Type: general – SubjectFull: Feature extraction Type: general Titles: – TitleFull: Digital Innovation in Environmental Art Design: The Combination of CAD and Multimodal Fusion Technology. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Mei Bai IsPartOfRelationships: – BibEntity: Dates: – D: 04 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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