A Rice Leaf Disease Image Dataset for Multi-Class Disease Classification
Description
This dataset contains images of rice leaves representing multiple disease and healthy classes. The dataset was prepared for research on automated rice leaf disease identification and classification using computer vision and deep learning techniques. It contains images from nine categories: Bacterial Leaf Blight, Brown Spot, Rice Hispa, Leaf Blast, Leaf Scald, Tungro, Neck Blast, Narrow Brown Spot, Sheath Blight, and Healthy leaves. The dataset contains 6,758 images in total, distributed across the following categories: Bacterial Leaf Blight: 785 images Brown Spot: 761 images Rice Hispa: 770 images Leaf Blast: 521 images Leaf Scald: 514 images Tungro: 556 images Neck Blast: 677 images Narrow Brown Spot: 767 images Sheath Blight: 608 images Healthy: 753 images The dataset can be used for research in rice crop disease classification, plant disease recognition, agricultural computer vision, deep learning, and explainable artificial intelligence. The dataset is intended to support the development and evaluation of automated approaches for identifying rice leaf diseases from images.
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Institutions
- Dhaka International UniversityDhaka Division, Dhaka