Rice Disease Correspondence Labels for Computer Vision Model Evaluation

A correspondence dataset of rice disease labels, likely used for training and evaluating the ECL-RTDETR detection model described in the associated research. The dataset was authored by Yaojun Zhang and last updated on June 3, 2026. It is a small dataset, 5.5 KB in size, and is available in XLS format.

Use Cases

• Evaluating rice disease detection model performance based on the correspondence labels
• Training lightweight vision models for agricultural monitoring based on the described disease detection task
• Benchmarking detection speed and computational efficiency in smart agriculture applications

Strengths

• Dataset is openly licensed under CC-BY-4.0
• Associated research paper describes a model achieving a 0.7% improvement in [email protected] and a 22.2 FPS increase in detection speed

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Description metadata is limited; actual data quality requires manual inspection after download

Provenance

Source

Yaojun Zhang

Freshness

Last updated 2026-06-03 17:54:28; freshness should be verified