A Survey on Deep Learning in Agriculture

Abstract

In multidisciplinary agricultural technology domain, deep learning opens up new possibilities for information research. This review paper presents 72 article and projects that use deep learning techniques to solve agricultural problems. We look at the agricultural problems being studied, the frameworks and models used, source of data, pre-processed data, and overall output based on the measurement that is used at the development process. We also compare deep learning to other common techniques to see if there are any variations in classification or regression results. In contrast to certain other widely used image processing methods, our results show that high accuracy are achieved by using deep learning.