AMCD: A multi-domain agricultural crop and flower image dataset for deep learning-based classification
Md Ahsan Karim, Md Tanjum An Tashrif, Shahariar Hossain Mahir, Md Kowsar Ahmed, Umme Sara, Mohammad Shorif Uddin, Tufayel Haque Raha · 2026
Read AMCD: A multi-domain agricultural crop and flower image dataset for deep learning-based classification by Md Ahsan Karim, Md Tanjum An Tashrif, Shahariar Hossain Mahir, Md Kowsar Ahmed, Umme Sara, Mohammad Shorif Uddin, Tufayel Haque Raha (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13311333.txt.
Description
Md Ahsan Karim and co-authors release a 2026 image dataset of farm crops and flowers from Bangladesh for training classification software. The set is named AMCD, short for Agricultural Multidisciplinary Collection Dataset.
The set holds 5405 photos sorted into four groups: fruits, vegetables, flowers, and crops or grains, with 77 subgroups in all. Photos were taken with phone cameras at farms, markets, and gardens in three districts near Dhaka in early 2025. Images were cleaned, squared, and lightly boosted where a class ran short. The set can train farm apps, test models, or serve as healthy-plant reference pictures.
Catalog record
| CREATOR | Md Ahsan Karim, Md Tanjum An Tashrif, Shahariar Hossain Mahir, Md Kowsar Ahmed, Umme Sara, Mohammad Shorif Uddin, Tufayel Haque Raha |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 18807 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |