Bayanmunkh Odgerel

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About

Bayanmunkh Odgerel is a researcher specializing in sensor-based human-computer interaction, decision fusion under uncertainty, and computer vision. Their work bridges hardware sensing and algorithmic intelligence, with a focus on improving how machines perceive and respond to human actions and environmental changes. In a notable contribution, Odgerel proposed a novel hand gesture recognition method using an infrared proximity sensor array combined with fuzzy logic classification, enabling more intuitive device control without traditional cameras. They also advanced multi-evidence decision-making by developing an improved Dempster-Shafer algorithm that addresses partial conflict measurement, enhancing the reliability of sensor fusion in robotics and autonomous systems. Additionally, Odgerel tackled real-world vision challenges by creating techniques for sudden illumination change detection and image contrast enhancement, improving visual processing under dynamic lighting. Each of these key papers has garnered 3 citations, reflecting foundational work that continues to inform developments in gesture interfaces, evidence theory, and adaptive imaging. Odgerel’s research demonstrates a consistent commitment to making computational systems more responsive and robust in practical, everyday environments.