ArticlePlant methods2019
Deep learning for image-based large-flowered chrysanthemum cultivar recognition.
Article in Plant methods, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
- Accurate Identification ofPlants (Basel, Switzerland) · 2026Article
- Chrysanthemum classification via color space fusion transformer.Scientific reports · 2026Article
- RGB imaging-based evaluation of waterlogging tolerance in cultivated and wild chrysanthemums.Plant phenomics (Washington, D.C.) · 2025Article
- Sulfur-Fumigated Ginger Identification Method Based on Meta-Learning for Different Devices.Foods (Basel, Switzerland) · 2024Article
- Species identification through deep learning and geometrical morphology in oaks (Ecology and evolution · 2024Article
- Chrysanthemum classification method integrating deep visual features from both the front and back sides.Frontiers in plant science · 2024Article
- A deep learning approach to track Arabidopsis seedlings' circumnutation from time-lapse videos.Plant methods · 2023Article
- Image dataset of tea chrysanthemums in complex outdoor scenes.Frontiers in plant science · 2023Article
- Medicinal Chrysanthemum Detection under Complex Environments Using the MC-LCNN Model.Plants (Basel, Switzerland) · 2022Article
- YOLO-VOLO-LS: A Novel Method for Variety Identification of Early Lettuce Seedlings.Frontiers in plant science · 2022Article
- Multi-Information Model for Large-Flowered Chrysanthemum Cultivar Recognition and Classification.Frontiers in plant science · 2022Article
- Tea Chrysanthemum Detection by Leveraging Generative Adversarial Networks and Edge Computing.Frontiers in plant science · 2022Article
- Metric learning for image-based flower cultivars identification.Plant methods · 2021Article
- Applications of deep-learning approaches in horticultural research: a review.Horticulture research · 2021Review
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4 authors.
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Abstract
backgroundCultivar recognition is a basic work in flower production, research, and commercial application. Chinese large-flowered chrysanthemum (
resultsWe propose deep learning models with two networks VGG16 and ResNet50 to recognize large-flowered chrysanthemum. Dataset A comprising 14,000 images for 103 cultivars, and dataset B comprising 197 images from different years were collected. Dataset A was used to train the networks and determine the calibration accuracy (Top-5 rate of above 98%), and dataset B was used to evaluate the model generalization performance (Top-5 rate of above 78%). Moreover, gradient-weighted class activation mapping (Grad-CAM) visualization and feature clustering analysis were used to explore how the deep learning model recognizes chrysanthemum cultivars.
conclusionDeep learning method applied to cultivar recognition is a breakthrough in horticultural science with the advantages of strong recognition performance and high recognition speed. Inflorescence edge areas, disc floret areas, inflorescence colour and inflorescence shape may well be the key factors in model decision-making process, which are also critical in human decision-making.
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