Abstract
The pattern on the costumes and brocades of ethnic minorities are of profound significance, but they are various and often composed of many kinds of patterns. It is not accurate and time-consuming to classify them only by artificial methods. Taking Yao’s pattern symbols as an example, this paper collects and arranges the pattern pictures on clothing and brocade, preprocesses the pictures and labels the patterns on the processed pictures according to the preliminary classification. After the data set is made, the data set is trained and tested by Faster R-CNN algorithm. The results show that this method can effectively identify and classify the patterns of Yao nationality while reducing the time-consuming, and the average accuracy can reach 88.71%. It provides a useful exploration to help more ethnic minorities realize the intelligent classification of patterns.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.