Meisam Teimouri

Qazvin Islamic Azad University, Qazvin University of Medical Sciences

Papers

Total Citations

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About

Meisam Teimouri is a leading researcher in robotics and artificial intelligence, with a primary focus on real-time perception and autonomous localization for humanoid robots. His most impactful work, "A Real-Time Ball Detection Approach Using Convolutional Neural Networks" (2019, 19 citations), introduces a deep learning framework that significantly enhances a robot's ability to detect and track objects in dynamic environments—a critical capability for competitive robotics. Teimouri also advanced self-localization techniques in his paper "A hybrid localization method for a soccer playing robot" (2016, 5 citations), where he refined Monte Carlo Localization methods to improve robot positioning accuracy under noisy sensor conditions. As a key contributor to the MRL team, he co-authored "MRL Champion Team Paper in Humanoid TeenSize League of RoboCup 2019" (2 citations), documenting the team's victory and innovative strategies. His work bridges theoretical probabilistic robotics with practical, real-world applications, making him a notable figure in the RoboCup community. Teimouri’s research continues to push the boundaries of autonomous robot performance, inspiring students and researchers in the fields of computer vision, localization, and multi-agent systems.