ArticleFrontiers in plant science2022
Deep Metric Learning-Based Strawberry Disease Detection With Unknowns.
Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Automatic Disease Detection from Strawberry Leaf Based on Improved YOLOv8.Plants (Basel, Switzerland) · 2024Article
- Embracing limited and imperfect training datasets: opportunities and challenges in plant disease recognition using deep learning.Frontiers in plant science · 2023Article
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3 authors.
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Abstract
There has been substantial research that has achieved significant advancements in plant disease detection based on deep object detection models. However, with unknown diseases, it is difficult to find a practical solution for plant disease detection. This study proposes a simple but effective strawberry disease detection scheme with unknown diseases that can provide applicable performance in the real field. In the proposed scheme, the known strawberry diseases are detected with deep metric learning (DML)-based classifiers along with the unknown diseases that have certain symptoms. The pipeline of our proposed scheme consists of two stages: the first is object detection with known disease classes, while the second is a DML-based post-filtering stage. The second stage has two different types of classifiers: one is softmax classifiers that are only for known diseases and the
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