An overview of deep learning in agriculture

Deep learning (DL) is a cutting-edge image processing and big data analysis method with enormous promise. Deep learning is a relatively new technique in the agricultural sector, but it has already shown to be effective in other fields. This article examines how various deep learning methods have been used to numerous agricultural issues, including disease detection and identification, fruit/plant categorization, and fruit counting, among other things. The article examines the models used, the data source, the results of each research, the hardware used, and the potential of real-time application to investigate future integration with autonomous robotic platforms. The findings show that deep learning produces high-accuracy results that, with a few exceptions, outperform conventional image processing methods in terms of precision.