Proceedings Paper
Dense learning by high dimensional SOMs composed of input-output fusion vectors for interactive image segmentation| Format | Member Price | Non-Member Price |
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Paper Abstract
This study proposes an interactive image segmentation method based on high dimensional self organizing maps (SOMs). The proposed method was applied to gray-scale and color images. The experimental results demonstrated that higher dimensional SOMs were able to achieve more accurate segmentation.
Paper Details
Date Published: 22 March 2019
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110492L (22 March 2019); doi: 10.1117/12.2520491
Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110492L (22 March 2019); doi: 10.1117/12.2520491
Show Author Affiliations
Hotaka Takizawa, Univ. of Tsukuba (Japan)
Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)
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