Anuchart Srisiriwat
Papers
2
Total Citations
17
H-Index
2
About
Anuchart Srisiriwat is an emerging researcher in robotics and intelligent control systems, with a focus on enhancing automation through computer vision and fuzzy logic. His work in robotic vision, particularly the 2023 study "Evaluation of Single and Dual Image Object Detection through Image Segmentation Using ResNet18," has garnered 13 citations for its practical approach to improving object detection accuracy in industrial settings. By leveraging ResNet18-based image segmentation, Srisiriwat demonstrated a method to efficiently extract objects from backgrounds, a critical step for real-time automation applications. In parallel, his comparative study of Takagi-Sugeno-Kang and Mamdani algorithms in Type-1 and Interval Type-2 fuzzy control for self-balancing wheelchairs (4 citations) showcases his versatility in control systems. This work, simulated in MATLAB, provides valuable insights into the performance of different fuzzy logic controllers for assistive mobility devices. Srisiriwat’s contributions bridge theoretical advances and practical deployment, making his research particularly relevant for students and engineers working on autonomous systems and human-assistive robotics.
Research Focus
Key Achievements
Top Papers
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