Study of flower image classification using deep learning to support agricultural pollination

Abstract

In smart agriculture, research and development is advanced by robots performing agricultural works instead of humans. Agricultural works requires experience and the human sense of sight and touch. In our study, experience and the sense of sight are replaced by machine learning. We developed a deep learning classification method and implemented it for tomato flower pollination classification in the agricultural field.