Bawornsak Sakulkueakulsuk

King Mongkut's University of Technology Thonburi

Papers

Total Citations

H-Index

About

Bawornsak Sakulkueakulsuk is a researcher whose work bridges robotics and computer vision, with key contributions in open-source hardware design and deep learning for text recognition. His most notable work, "Design of an Open Source Anthropomorphic Robotic Finger for Telepresence Robot" (2021, 2 citations), presents a 3D-printable, three-jointed finger with two active degrees of freedom, designed for teleoperation systems. This low-cost, easily fabricated design advances accessible robotics by enabling precise, human-like manipulation for telepresence applications. In computer vision, his paper "Word Recognition in Captured Images by CNN Trained with Synthetic Images" (2018, 2 citations) tackles the challenge of rapid, accurate word recognition in natural scenes for tasks like robotic navigation and geocoding. By training a convolutional neural network on synthetic images, his method achieves high accuracy across multiple languages, demonstrating a practical approach to overcoming data scarcity. While his citation counts are modest, Sakulkueakulsuk’s work exemplifies impactful, reproducible research—offering open-source solutions that lower barriers to entry in robotics and providing scalable deep learning techniques for real-world vision tasks. His contributions are particularly valuable for students and researchers seeking accessible, deployable methods in telepresence and automated text recognition.