Project-AgML/rice_field_weed_classification

Rice Field Weed Classification

A dataset for weed classification in rice fields. The dataset contains 3,632 images across 11 classes: Images per class:

• Alternanthera philoxeroide: 106
• Centella asiatica: 404
• Commelina benghalensis: 316
• Cyperus ochraceus: 190
• Fimbristylis littoralis: 168
• Ipomoea aquatic: 897
• Marsilea minuta: 346
• Panicum repens: 294
• Paspalum scrobiculatum: 345
• Pteris vittata: 221
• Synedrella nodiflora: 345

This dataset is indexed on https://project-agml.github.io/ as part of the AgML python library.

Citation

@article{ali2024comprehensive,
  title={A comprehensive dataset of rice field weed detection from Bangladesh},
  author={Ali, Md Sawkat and Rashid, Mohammad Rifat Ahmmad and Hossain, Tasnim and Kabir, Md Ahsan and Kamrul, Md and Aumy, Sayam Hossain Bhuiyan and Mridha, Mehedi Hasan and Sajeeb, Imam Hossain and Islam, Mohammad Manzurul and Jabid, Taskeed},
  journal={Data in Brief},
  volume={57},
  pages={110981},
  year={2024},
  publisher={Elsevier}
}

Ali, Sawkat; Ahmmad Rashid, Mohammad Rifat ; Hossain Orpa, Tasnim; Kabir, Md Ahsan; Kamrul, Md; Bhuiyan Aumy , Sayam Hossain ; Mridha, Mehedi Hasan ; Sajeeb, Imam Hossain ; Manzurul Islam, Mohammad ; Jabid, Taskeed (2024), “A comprehensive dataset of rice field weed detection from Bangladesh”, Mendeley Data, V4, doi: 10.17632/mt72bmxz73.4