Hyperparameter Optimization for Tomato Leaf Disease Recognition Based on YOLOv11m Article Swipe
Yong-Suk Lee
,
Maheshkumar Prakash Patil
,
Jeong Gyu Kim
,
Yong Bae Seo
,
Dong-Hyun Ahn
,
Gun‐Do Kim
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/plants14050653
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/plants14050653
The automated recognition of disease in tomato leaves can greatly enhance yield and allow farmers to manage challenges more efficiently. This study investigates the performance of YOLOv11 for tomato leaf disease recognition. All accessible versions of YOLOv11 were first fine-tuned on an improved tomato leaf disease dataset consisting of a healthy class and 10 disease classes. YOLOv11m was selected for further hyperparameter optimization based on its evaluation metrics. It achieved a fitness score of 0.98885, with a precision of 0.99104, a recall of 0.98597, and a [email protected] of 0.99197. This model underwent rigorous hyperparameter optimization using the one-factor-at-a-time (OFAT) algorithm, with a focus on essential parameters such as batch size, learning rate, optimizer, weight decay, momentum, dropout, and epochs. Subsequently, random search (RS) with 100 configurations was performed based on the results of OFAT. Among them, the C47 model demonstrated a fitness score of 0.99268 (a 0.39% improvement), with a precision of 0.99190 (0.09%), a recall of 0.99348 (0.76%), and a [email protected] of 0.99262 (0.07%). The results suggest that the final model works efficiently and is capable of accurately detecting and identifying tomato leaf diseases, making it suitable for practical farming applications.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/plants14050653
- OA Status
- gold
- Cited By
- 15
- References
- 70
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4407812969
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4407812969Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/plants14050653Digital Object Identifier
- Title
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Hyperparameter Optimization for Tomato Leaf Disease Recognition Based on YOLOv11mWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-02-21Full publication date if available
- Authors
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Yong-Suk Lee, Maheshkumar Prakash Patil, Jeong Gyu Kim, Yong Bae Seo, Dong-Hyun Ahn, Gun‐Do KimList of authors in order
- Landing page
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https://doi.org/10.3390/plants14050653Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.3390/plants14050653Direct OA link when available
- Concepts
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Hyperparameter, Dropout (neural networks), Random forest, Recall, Artificial intelligence, Hyperparameter optimization, Machine learning, Precision and recall, Computer science, Pattern recognition (psychology), Statistics, Mathematics, Support vector machine, Psychology, Cognitive psychologyTop concepts (fields/topics) attached by OpenAlex
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15Total citation count in OpenAlex
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2025: 15Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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