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

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

IntroductionRising global populations and climate change necessitate increased agricultural productivity. Most studies on rice panicle detection using imaging technologies rely on single-time-point analyses, failing to capture the dynamic changes in panicle coverage and their effects on yield. There...

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Main Authors: Hyeok-Jin Bak, Eun-Ji Kim, Ji-Hyeon Lee, Sungyul Chang, Dongwon Kwon, Woo-Jin Im, Woon-Ha Hwang, Jae-Ki Chang, Nam-Jin Chung, Wan-Gyu Sang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-08-01
Series:Frontiers in Plant Science
Subjects:
rice
phenotyping
deep learning
semantic segmentation
yield prediction
timeseries analysis
Online Access:https://www.frontiersin.org/articles/10.3389/fpls.2025.1611653/full
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https://www.frontiersin.org/articles/10.3389/fpls.2025.1611653/full

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