Hong Hai Hoang

Hanoi University of Science and Technology

Papers

Total Citations

H-Index

About

Hong Hai Hoang is a rising researcher at the intersection of agricultural robotics and computer vision, with a focus on deploying deep learning for real-world automation. His work centers on object detection, instance segmentation, and synthetic data generation—techniques that enable machines to perceive and interact with their environments. Hoang’s most cited papers, each garnering 4 citations, showcase his early but impactful contributions. In "Design of Agriculture Robot for Tomato Plants in Green House," he addresses the challenge of automating crop monitoring and harvesting in controlled environments. His study "Application of Synthetic Data on Object Detection Tasks" tackles a critical bottleneck in computer vision: the need for large, diverse, and labeled datasets. By generating artificial training data, Hoang demonstrates a scalable solution to improve detection accuracy without costly manual annotation. In "Accurate Instance-Based Segmentation for Boundary Detection in Robot Grasping Application," he refines segmentation algorithms to precisely delineate object boundaries, a key requirement for reliable robotic manipulation. Together, these works highlight Hoang’s commitment to bridging simulation and reality, advancing both agricultural technology and the foundational methods that power autonomous systems.