Lemon Leaf Disease Dataset
- Citation Author(s):
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Benjamin Doh (Jiangsu University, China)
- Submitted by:
- Benjamin Doh
- Last updated:
- DOI:
- 10.21227/ft7z-ts71
- Data Format:
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Abstract
The Lemon Leaf Disease Dataset (LLDD) is a high-quality image dataset designed for training and evaluating machine learning models for lemon leaf disease classification. The dataset contains 9 classes of images of healthy and diseased lemon leaves, such as; Anthracnose. Bacterial Blight, Citrus Canker, Curl Virus, Deficiency Leaf, Dry Leaf, Healthy Leaf, Sooty Mould, Spider Mites, making it suitable for tasks such as plant disease instance segmentation, detection, image classification, and deep learning applications in agriculture. This dataset is manually annotated and converted into a YOLO format for segmentaton, detection, classification and other deep learning applications.
Instructions:
The Lemon Leaf Disease Dataset (LLDD) is a high-quality image dataset designed for training and evaluating machine learning models for lemon leaf disease classification. The dataset contains 9 classes of images of healthy and diseased lemon leaves, such as; Anthracnose. Bacterial Blight, Citrus Canker, Curl Virus, Deficiency Leaf, Dry Leaf, Healthy Leaf, Sooty Mould, Spider Mites, making it suitable for tasks such as plant disease instance segmentation, detection, image classification, and deep learning applications in agriculture. This dataset is manually annotated and converted into a YOLO format for segmentaton, detection, classification and other deep learning applications.
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