Guava Leaf Disease Image Collection

GLDD provides labeled images of guava leaves for disease classification tasks in precision agriculture. The dataset's size, creator, and update date are not specified in the provided information.

Use Cases

• Train convolutional neural networks to classify disease states from leaf image features.
• Benchmark image segmentation models against leaf lesion patterns.
• Develop mobile applications for farmers to diagnose guava diseases using camera input.

Strengths

• Designed specifically for guava leaf disease classification, a targeted agricultural application.

Limitations

• Dataset size, row count, and image resolution are unknown, limiting reproducibility assessment.
• Potential class imbalance or limited disease variety cannot be evaluated without sample data.

Provenance

Collection Method

Presumably involves capturing images of guava leaves in agricultural settings, but method is unspecified.