Paper Contents
Abstract
More than half of the people in the world eat rice, so it needs to be properly labeled so that growing methods can be made better and food quality stays high. The normal ways of telling the difference between types of rice are hard to do and take a long time. CNNs, and more specifically the ResNet-50 design, will be used to carefully put different types of rice into groups. This is the main goal of the study. A lot of data has been used to show that ResNet-50 is very good at putting pictures of rice into different groups. This shows that ResNet-50 could be useful in precision farming since it can quickly and correctly group different types of rice. ResNet-50 could make gardening better and make sure that everyone in the world has safe food. Getting rid of the need for hard physical work and skewed opinion helps with this.
Copyright
Copyright © 2024 sanket kumar. This is an open access article distributed under the Creative Commons Attribution License.
