Hongbin Suo

Henan University of Science and Technology

Papers

Total Citations

H-Index

About

Hongbin Suo is a researcher whose work lies at the intersection of agricultural robotics and deep learning, with a primary focus on autonomous navigation for precision farming. His most-cited paper, "An Inter-Ridge Navigation Path Extraction Method Based on Res2net50 Segmentation Model" (2023, 5 citations), addresses a critical challenge in field robotics: extracting reliable navigation lines from complex agricultural environments. Suo’s key contribution is a deep learning-based approach that overcomes the poor real-time performance and light interference that plague traditional navigation path recognition systems. By leveraging the Res2Net50 segmentation model, his method enhances both the speed and robustness of ridge detection, enabling agricultural robots to operate more effectively under variable field conditions. This work is particularly notable for its potential to improve the autonomy and efficiency of farming equipment, reducing the need for human intervention. While his citation count is still growing, Suo’s research represents an important step toward practical, AI-driven solutions in agriculture, offering a foundation for future innovations in autonomous crop management and field navigation.