Distinguishing Hand Drawing Style Based on Multilevel Analytics Framework

Author

Xu, Hui

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