Skip to main content
SIGraDi 2024 | Biodigital Intelligent Systems

Full Program »

Machine Learning For Classification of Bamboo Woven Design

Applications of bamboo woven design in the craft industry around the world are predominantly informed by highly trained artisanal skills. The research is conducted by a combination of primary data collection, includes collecting typical patterns from a design library and an interview with an expert bamboo artisan. Secondary data collection serves as the point of departure of the dataset, the 14 identified patterns. The primary objective of this study is to facilitate an accessible entry point for novice designers to engage with bamboo woven design, thereby preserving the essence of traditional bamboo weaving craftsmanship. Evaluation of the model through key metrics indicates the attainment of high accuracy and precision values. However, there exists an opportunity for future enhancement focused on improving the moderate 'loss' metric, elevating the recall value, and striking a delicate balance between precision and recall values. For forthcoming studies, authors aim to further refine the recognition system.

Mia Tedjosaputro
Xi'an Jiaotong - Liverpool University
China

Evangel Solomon
Xi'an Jiaotong - Liverpool University
China

Farkhondeh Vahdati
Xi'an Jiaotong - Liverpool University
China

Kiarash Amiri
Malek Ashtar University of Technology
Iran

 

Privacy Policy

Powered by OpenConf®
Copyright ©2002-2024 Zakon Group LLC