Tobacco Dataset for crop/weed classification

We have acquired a new tobacco-weed dataset using a Mavic Mini drone. Eight fields of tobacco crop are captured in Mardan, Khyber Pakhtunkhwa, Pakistan. At different growth stages these eight fields are captured at crop age of 15 to 40 days approximately. Data is captured at 1920×1080-pixel resolution. Dataset is captured at an average altitude of 4 meters with ground sampling distance of 0.1 cm/pixel.

Find Details in attached Research papers

Citation Request: if you use these datasets in your research or projects by any means, please cite following publications.

1) Patch-wise weeds coarse segmentation mask from aerial imagery of sesame crop
(Published in Computers and Electronics in Agriculture 2022, HEC Recognized W category, Impact factor 6.757, Q1)
2) Towards automated weed detection through two-stage semantic segmentation of tobacco and weed pixels in aerial Imagery
(Published in Smart Agricultural Technology (A companion journal of Computers and Electronics in Agriculture))
3) A Patch-Image Based Classification Approach for Detection of Weeds in Sugar Beet Crop
(Published in IEEE Access, Impact factor 3.1, Q1)

Acknowledgement Request
This work is funded by the Higher Education Commission of Pakistan and the National center for Robotics and Automation (DF-1009–31). Please Acknowledge.

Steps to Access Mendeley datasets
1. Click on the link
2. The link with ask you to sign in or register with institutional email.
3. Use your institutional/organization email to register and then sign in.
4. Once sign in, dataset will be visible in compressed folders
5. Download and unzip/umcompress folder
6. Use dataset in your research as you see fit (folders contains original images, and their labeled groundtruths, along with binary vegetation masks. In groundtruths background have label value of 0, crop have label 1 and weeds have label of 2. maskref subfolders shows labelled data for visualization)

Find More datasets and published articles in Related Links