🇧🇩 Bangladeshi Crops Disease Dataset (BCDD)

Official dataset for the IEEE ECCE 2025 paper:

"Plant Disease Recognition from the Perspective of Bangladesh: A Comparative Study of Deep Learning Models and Ensemble Techniques"

🚀 Associated Resources

Resource	Link
GitHub Code
Kaggle Source
Paper Abstract

🔬 Collection Methodology

The dataset is a curated subset of three public repositories:

1. Wheat Leaf Disease Dataset (6,134 images)
2. Rice Leaf Disease Dataset (2,627 images)
3. Plant Village Dataset

It focuses on 5 crops (Corn, Potato, Rice, Tomato, Wheat) relevant to Bangladesh. Images were resized to 96x96 pixels and augmented using rotation, flipping, and grayscale conversion to ensure robustness.

🐍 Quick Load

You can load this dataset directly in Python using the Hugging Face datasets library:

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("musfiqurtuhin/BCDD")

# View a training example
print(dataset['train'][0])

📝 Citation

If you use this dataset in your research, please cite our ECCE 2025 paper:

@InProceedings{11013222,
  author={Rahman, Md. Musfiqur and Tusher, Md Mahbubur Rahman and Rinky, Susmita Roy and Mokit, Junaid Rahman and Biswas, Sudipa},
  booktitle={2025 International Conference on Electrical, Computer and Communication Engineering (ECCE)}, 
  title={Plant Disease Recognition from the Perspective of Bangladesh: A Comparative Study of Deep Learning Models and Ensemble Techniques}, 
  year={2025},
  pages={1-6},
  doi={10.1109/ECCE64574.2025.11013222}
}