Revolutionizing Agriculture with Deep Learning Current Trends and Future Directions

Abstract

Deep learning creates new opportunities for information study in the diverse field of agricultural technology. A total of 61 publications and initiatives using deep learning to address issues in agriculture are reviewed in this study. The agricultural issues under investigation, the frameworks and models employed, the data source, pre-processed data, and total output depending on the metrics employed at each work site are examined. To ascertain potential disparities in classification or regression outcomes, a comparison is conducted between deep learning and other widely utilized methods. The findings demonstrate that deep learning can produce results with excellent accuracy compared to several other popular image processing techniques.