Year: 2024
Type: article
Abstract: The Date fruit is a major crop grown in Middle East. Pakistan was ranked in 5th position in the year 2022 by the Food and Agriculture Organization (FAO). The dates are different from each other due to color, size, texture, and shape with respect to region(or it varies from region to region). The classification, sorting, and separating of date fruit is a crucial process in the industry as manual process is time-consuming, laborious, and inaccurate. A state of art dataset has been used in this research work. for training and testing of models. The Convolutional Neural Network (CNN) based intelligent system based on five date fruit varieties has been proposed. The proposed system classifies five date fruit varieties (Aseel, Dandhi, Fasli Toto, Gajar, and Kupro) efficiently and effectively. In fact, three deep learning models have been trained and tested; each one has achieved a different level of accuracy in terms of five different classes. The novel dataset was collected by the authors of this study to develop proposed system. The highest performance of the proposed system on five different classes were 99.2%, 99.4%, 99.4% and 99.2% for average accuracy, precision, recall and F1-score respectively.
Institutions: Shah Abdul Latif University, Sukkur IBA University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
OpenAlex ID: W4405655415