Unseok相关文献与解析，生知库 | 链接生命科学的每一步

AraDQ: an automated digital phenotyping software for quantifying disease symptoms of flood-inoculated Arabidopsis seedlings

AraDQ：一种用于量化水淹接种拟南芥幼苗疾病症状的自动化数字表型分析软件

期刊:Plant Methods

影响因子:4.4

doi:10.1186/s13007-024-01171-w

Lee, Jae Hoon; Lee, Unseok; Yoo, Ji Hye; Lee, Taek Sung; Jung, Je Hyeong; Kim, Hyoung Seok

发表日期：2024

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A Novel Method for Quantifying Plant Morphological Characteristics Using Normal Vectors and Local Curvature Data via 3D Modelling-A Case Study in Leaf Lettuce

一种利用法向量和局部曲率数据通过三维建模量化植物形态特征的新方法——以莴苣为例

期刊:Sensors

影响因子:3.5

doi:10.3390/s23156825

Wada, Kaede C; Hayashi, Atsushi; Lee, Unseok; Tanabata, Takanari; Isobe, Sachiko; Itoh, Hironori; Maeda, Hideki; Fujisako, Satoshi; Kochi, Nobuo

发表日期：2023

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Time-Series Growth Prediction Model Based on U-Net and Machine Learning in Arabidopsis

基于U-Net和机器学习的拟南芥时间序列生长预测模型

期刊:Frontiers in Plant Science

影响因子:4.8

doi:10.3389/fpls.2021.721512

Chang, Sungyul; Lee, Unseok; Hong, Min Jeong; Jo, Yeong Deuk; Kim, Jin-Baek

发表日期：2021

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TheLNet270v1 - A Novel Deep-Network Architecture for the Automatic Classification of Thermal Images for Greenhouse Plants

LNet270v1——一种用于温室植物热图像自动分类的新型深度网络架构

期刊:Frontiers in Plant Science

影响因子:4.8

doi:10.3389/fpls.2021.630425

Islam, Md Parvez; Nakano, Yuka; Lee, Unseok; Tokuda, Keinichi; Kochi, Nobuo

发表日期：2021

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High-Throughput Phenotyping (HTP) Data Reveal Dosage Effect at Growth Stages in Arabidopsis thaliana Irradiated by Gamma Rays

高通量表型分析（HTP）数据揭示了伽马射线照射拟南芥生长阶段的剂量效应

期刊:Plants-Basel

影响因子:4.1

doi:10.3390/plants9050557

Chang, Sungyul; Lee, Unseok; Hong, Min Jeong; Jo, Yeong Deuk; Kim, Jin-Beak

发表日期：2020

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A Feasibility Study of Tablet-Based Eye Movement Assessment Using a Built-In Camera: A Pilot Study

基于平板电脑内置摄像头的眼动评估可行性研究：一项试点研究

Development of a deep-learning phenotyping tool for analyzing image-based strawberry phenotypes

开发一种基于深度学习的草莓表型分析工具，用于分析基于图像的草莓表型

AraDQ: an automated digital phenotyping software for quantifying disease symptoms of flood-inoculated Arabidopsis seedlings

AraDQ：一种用于量化水淹接种拟南芥幼苗疾病症状的自动化数字表型分析软件

A Novel Method for Quantifying Plant Morphological Characteristics Using Normal Vectors and Local Curvature Data via 3D Modelling-A Case Study in Leaf Lettuce

一种利用法向量和局部曲率数据通过三维建模量化植物形态特征的新方法——以莴苣为例

Time-Series Growth Prediction Model Based on U-Net and Machine Learning in Arabidopsis

基于U-Net和机器学习的拟南芥时间序列生长预测模型

TheLNet270v1 - A Novel Deep-Network Architecture for the Automatic Classification of Thermal Images for Greenhouse Plants

LNet270v1——一种用于温室植物热图像自动分类的新型深度网络架构

High-Throughput Phenotyping (HTP) Data Reveal Dosage Effect at Growth Stages in Arabidopsis thaliana Irradiated by Gamma Rays

高通量表型分析（HTP）数据揭示了伽马射线照射拟南芥生长阶段的剂量效应