Publications by authors named "Shengcao Huang"
Front Plant Sci
August 2024
Article Synopsis
- - The text discusses the importance of real-time corn yield monitoring for precision agriculture, highlighting limitations in existing methods that use photoelectric sensors which don't account for varying corn stacking patterns due to feeding volume, terrain, and speed.
- - To address these issues, the researchers used EDEM simulation to analyze corn stacking patterns and developed a real-time monitoring system with machine learning models, including Deep Neural Networks (DNN), Gradient Boosting Machine (GBM), and Random Forest (RF), which have been rigorously validated.
- - The results showed that the DNN model outperformed the others with a very high coefficient of determination (R) of 0.998 and an average accuracy of 97.85%, demonstrating the effectiveness of
