An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis. by Unseok Lee, Sungyul Chang, Gian Anantrio Putra, Hyoungseok Kim, Dong Hwan Kim

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Time-Series Growth Prediction Model Based on U-Net and Machine Learning in Arabidopsis by Sungyul Chang, Unseok Lee, Min Jeong Hong, Yeong Deuk Jo, Jin-Baek Kim

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Lettuce Growth Pattern Analysis Using U-Net Pre-Trained with <i>Arabidopsis</i> by Sungyul Chang, Unseok Lee, Min Jeong Hong, Yeong Deuk Jo, Jin-Baek Kim

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High-Throughput Phenotyping (HTP) Data Reveal Dosage Effect at Growth Stages in <i>Arabidopsis thaliana</i> Irradiated by Gamma Rays by Sungyul Chang, Unseok Lee, Min Jeong Hong, Yeong Deuk Jo, Jin-Baek Kim

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Comparative mapping of the wild perennial Glycine latifolia and soybean (G. max) reveals extensive chromosome rearrangements in the genus Glycine. by Sungyul Chang, Carrie S Thurber, Patrick J Brown, Glen L Hartman, Kris N Lambert, Leslie L Domier

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Implication of high variance in germplasm characteristics by Ju-Kyung Yu, Sungyul Chang, Gyung Deok Han, Seong-Hoon Kim, Jinhyun Ahn, Jieun Park, Yoonha Kim, Jaeyoung Kim, Yong Suk Chung

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