Pattern segmentation based on PoolNet and boundary connectivity

Autor:	Gu Xiaohong, Shang Shuyuan
Jazyk:	English<br />French
Rok vydání:	2023
Předmět:	significance test boundary connectivity pattern segmentation poolnet Social Sciences
Zdroj:	SHS Web of Conferences, Vol 166, p 01069 (2023)
Druh dokumentu:	article
ISSN:	2261-2424 20231660
DOI:	10.1051/shsconf/202316601069
Popis:	Traditional image segmentation algorithms need to design features manually. Therefore, based on the advantage of PoolNet in object detection, this paper proposes a clothing pattern segmentation algorithm combining PoolNet detection and boundary connectivity. This algorithm has more fine edges than traditional segmentation. Especially in the case of similar background before and after, we can get more complete pattern elements, and have better results in segmentation accuracy.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/8fccc3b3d6184deea02414f52afa1cae Zobrazit plný text záznamu View record in DOAJ