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Deep learning-based semantic segmentation for rice yield estimation by analyzing the dynamic change of panicle coverage.

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Bibliographic Details
Title:	Deep learning-based semantic segmentation for rice yield estimation by analyzing the dynamic change of panicle coverage.
Authors:	Bak HJ; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea., Kim EJ; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea., Lee JH; National Institute of Horticultural and Herbal Science, Rural Development Administration, Muan-gun, Republic of Korea., Chang S; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea., Kwon D; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea., Im WJ; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea., Hwang WH; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea., Chang JK; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea., Chung NJ; Department of Agronomy, Jeonbuk National University, Jeonju-si, Republic of Korea., Sang WG; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.
Source:	Frontiers in plant science [Front Plant Sci] 2025 Aug 14; Vol. 16, pp. 1611653. Date of Electronic Publication: 2025 Aug 14 (Print Publication: 2025).
Publication Type:	Journal Article
Journal Info:	Publisher: Frontiers Research Foundation Country of Publication: Switzerland NLM ID: 101568200 Publication Model: eCollection Cited Medium: Print ISSN: 1664-462X (Print) Linking ISSN: 1664462X NLM ISO Abbreviation: Front Plant Sci Subsets: PubMed not MEDLINE
Database:	MEDLINE Ultimate

Description
ISSN:	1664-462X
DOI:	10.3389/fpls.2025.1611653