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Distinguishing Hand Drawing Style Based on Multilevel Analytics Framework
Author
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-07
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Hand drawing is an indispensable professional skill in the fields of environmental design, industrial design, architectural engineering, civil engineering, and other engineering design education.
Students usually imitate masterpieces to practice basic skills, which is an important link for a beginner.
A system for digital management requires a function for an automatic recommendation task of different brushwork skill expressions.
Thus, the classification method for brushwork is to combine hand-crafted features generated by DCNN and then use the final features for input to a tree structure classification scheme.
The method improvement of the other deep learning models has effectiveness in distinguishing art ontology attributes.
American Psychological Association (APA)
Xu, Hui. 2020. Distinguishing Hand Drawing Style Based on Multilevel Analytics Framework. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1214701
Modern Language Association (MLA)
Xu, Hui. Distinguishing Hand Drawing Style Based on Multilevel Analytics Framework. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1214701
American Medical Association (AMA)
Xu, Hui. Distinguishing Hand Drawing Style Based on Multilevel Analytics Framework. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1214701
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214701