Wittayathawon Kanlaya

Papers

Total Citations

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About

Kanlaya Wittayathawon’s research centers on advancing robot vision and object recognition, with a particular focus on making visual systems robust to changing environmental conditions. Her most cited work, “Virtual object for evaluating Adaptable K-Nearest Neighbor method solving various conditions of object recognition” (2009), tackles a fundamental challenge in robotics: enabling machines to reliably identify objects under varying illumination, weather, and other dynamic factors. By introducing an adaptable K-Nearest Neighbor method and using virtual objects for systematic evaluation, she proposed a practical approach to improve recognition accuracy when conditions shift unpredictably. This contribution addresses a critical bottleneck in autonomous manipulation—robots must first “see” correctly before they can interact with their surroundings. While her citation count remains modest, the work reflects a thoughtful engagement with real-world variability in robotic perception, laying groundwork for more resilient vision systems. Wittayathawon’s research speaks to the intersection of machine learning and robotics, where even incremental improvements in adaptability can have meaningful implications for field deployment. Her focus on evaluating methods under diverse conditions underscores a commitment to practical, deployable solutions in artificial intelligence.