The original research article:
İ. Çınar and M. Koklu. Identification of rice varieties using machine learning algorithms. Journal of Agricultural Sciences, 28(2):307–325, 2022. doi: 10.15832/ankutbd.862482.
https://dergipark.org.tr/en/download/article-file/1513632
Import the images. Data can be found from (downloading starts as you press the link) https://www.muratkoklu.com/datasets/vtdhnd09.php Save the data folders 'Arborio', 'Basmati', 'Ipsala', 'Jasmine', and 'Karacadag' in 'data' folder. Take a random sample of 100 images from each rice species (i.e. 500 images in total). Use seed(50) for enabling reproducible results.
"""https://www.muratkoklu.com/datasets/vtdhnd09.php"""
1: KOKLU, M., CINAR, I. and TASPINAR, Y. S. (2021). Classification of rice varieties with deep learning methods. Computers and Electronics in Agriculture, 187, 106285.
DOI: https://doi.org/10.1016/j.compag.2021.106285
2: CINAR, I. and KOKLU, M. (2021). Determination of Effective and Specific Physical Features of Rice Varieties by Computer Vision In Exterior Quality Inspection. Selcuk Journal of Agriculture and Food Sciences, 35(3), 229-243.
DOI: https://doi.org/10.15316/SJAFS.2021.252
3: CINAR, I. and KOKLU, M. (2022). Identification of Rice Varieties Using Machine Learning Algorithms. Journal of Agricultural Sciences, 28 (2), 307-325.
DOI: https://doi.org/10.15832/ankutbd.862482
4: CINAR, I. and KOKLU, M. (2019). Classification of Rice Varieties Using Artificial Intelligence Methods. International Journal of Intelligent Systems and Applications in Engineering, 7(3), 188-194.