Arabian Date Classification Using CNN Algorithm with Various Pre-trained Models

Abstract

The people of Bangladesh have a lack of knowledge to detect fruit so many consumers suffer when they go to buy fruit every day. We know it is very difficult for consumers to detect the class of date on their naked eyes. It is necessary to build a model that can predict the class of a date. We have been select computer vision terminology for properly classifying the data images. Here the random typical fruiting of images in our dataset is used. We used CNN for image classification here and the algorithm provides an optimal architecture through image classification. The CNN's algorithm works well for any image This method will help consumers to identify the dates. We use computer vision and object recognition image processing to create interactive real-world and thereby enhancing the user experience. The main goal of our research is to demonstrate the feasibility and test the effectiveness of the project and the focus of our project is to identify different types of dates and this can help a consumer to get an instant solution to the date fruit identification problem very easily. The validation accuracy proportions of our research contain 82.67%.