Development of a Cut Rose Longevity Prediction Model Using Thermography and Machine Learning
Author:
Affiliation:
1. Masters student, Graduate Department of Environmental Horticulture, Dankook University
2. Professor, Department of Environmental Horticulture and Landscape architecture, Environmental Horticulture major, Dankook University
Publisher
Korean Society of Horticultural Science
Subject
Horticulture,Horticulture
Link
https://www.hst-j.org/articles/pdf/doi/10.7235/HORT.20200061.pdf
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1. Development of a longevity prediction model for cut roses using hyperspectral imaging and a convolutional neural network;Frontiers in Plant Science;2024-01-10
2. Prediction of Vase Life through Correlation Analysis between Smart Greenhouse Environments by Cultivation Methods and Quality Characteristics of Cut Flowers in Standard Rose;Flower Research Journal;2023-12-31
3. Early Detection of Botrytis cinerea Infection in Cut Roses Using Thermal Imaging;Plants;2023-12-06
4. Classification of strawberry ripeness stages using machine learning algorithms and colour spaces;Horticulture, Environment, and Biotechnology;2023-10-02
5. Antimicrobial Effect of Slightly Acidic Electrolyzed (HOCl) Water on Botrytis cinerea of Cut Rose Flowers;Horticultural Science and Technology;2023-06-30
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