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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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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
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  Data: <searchLink fieldCode="AU" term="%22Bak+HJ%22">Bak HJ</searchLink>; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kim+EJ%22">Kim EJ</searchLink>; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Lee+JH%22">Lee JH</searchLink>; National Institute of Horticultural and Herbal Science, Rural Development Administration, Muan-gun, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Chang+S%22">Chang S</searchLink>; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Kwon+D%22">Kwon D</searchLink>; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Im+WJ%22">Im WJ</searchLink>; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Hwang+WH%22">Hwang WH</searchLink>; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Chang+JK%22">Chang JK</searchLink>; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Chung+NJ%22">Chung NJ</searchLink>; Department of Agronomy, Jeonbuk National University, Jeonju-si, Republic of Korea.<br /><searchLink fieldCode="AU" term="%22Sang+WG%22">Sang WG</searchLink>; National Institute of Crop and Food Science, Rural Development Administration, Wanju-gun, Republic of Korea.
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              Text: 2025 Aug 14
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