An Approach to Ripening of Pineapple Fruit with Model Yolo v5
Akhilesh Sharma, Ha Huy Cuong Nguyen, Thien Xuan Bui, Sachit Bhardwa, Đoàn Văn Thắng
Abstract
In the Fourth Industrial Revolution, Artificial Intelligence is being widely applied in society to improve the quality of life. Advanced technology is applied to industrialized and modernized models to improve the quality and increase the accuracy of production models. In the current agricultural model, humans are used as the main workforce, which is costly in terms of finance as well as human resources. The typical fruits of each region, especially pineapple, have a rather complicated ripening period. It is difficult to control and manage hundreds of hectares of fields. Therefore, in this paper, we propose to use deep learning models to assist in identifying and detecting the ripening period of pineapples to ensure that the care and harvest is carried out on time. Our best accuracy is observed over 95%.