Classification of Cumin, Fennel and Carom Using Transfer Learning
Document Type
Conference Proceeding
Publication Title
2022 5th International Conference on Signal Processing and Information Security, ICSPIS 2022
Abstract
Machine learning has become an important part of our daily lives. And, with the assistance of image processing, we can accomplish much more than before. Different types of seeds can be detected and classified. However, differentiating seeds is a difficult task. And, as the use of homemade medicine grows, it is critical to choose the right ingredient. Some may experience severe side effects. Cumin, fennel, and carom seed are all members of the same family and have similar appearances, making it easy for people to confuse one for the other. This study proposes an ML model based on image processing and transfer learning to distinguish between cumin, fennel, and carom. For training and testing purposes, a dataset of 360 images from each class was created.
First Page
46
Last Page
49
DOI
10.1109/ICSPIS57063.2022.10002538
Publication Date
1-1-2022
Recommended Citation
Siddiqui, Abdullah Ajaz; Sohail, Shahab Saquib; Areeb, Qazi; Mansoor, Wathiq; and Nafis, Md Tabrez, "Classification of Cumin, Fennel and Carom Using Transfer Learning" (2022). Computer Vision Faculty Publications. 288.
https://dclibrary.mbzuai.ac.ae/cvfp/288