Parsa Yarmohammadi
Papers
1
Total Citations
10
H-Index
1
About
Parsa Yarmohammadi is a researcher at the forefront of integrating robotics and artificial intelligence, with a primary focus on deep learning-driven automation and parallel robotic systems. His most-cited work, “Experimental Study on Chess Board Setup Using Delta Parallel Robot Based on Deep Learning” (2023, 10 citations), exemplifies his innovative approach to merging computer vision with robotic manipulation. In this study, Yarmohammadi demonstrates how a Delta parallel robot, guided by deep learning algorithms, can autonomously arrange a chessboard—a task that requires precise object detection, spatial reasoning, and dexterous control. This contribution highlights his broader expertise in developing intelligent robotic systems capable of performing routine, complex tasks with minimal human intervention. By combining state-of-the-art object detection with high-speed parallel robotics, Yarmohammadi’s work paves the way for more efficient automation in manufacturing, logistics, and service industries. His research not only advances the practical application of deep learning in robotics but also offers a scalable framework for future autonomous systems. With a growing citation record and a clear focus on real-world impact, Yarmohammadi is establishing himself as a promising voice in the fields of robotics and artificial intelligence.
Research Focus
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Top Papers
- 1