Muhamad Rezki Dwijayanto

Papers

Total Citations

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About

Muhamad Rezki Dwijayanto is a researcher specializing in computer vision and deep learning, with a particular focus on real-time object recognition and sports analytics. His most cited work, "Real-Time Object Recognition for Football Field Landmark Detection Based on Deep Neural Networks" (2019), introduces an innovative application of the YOLO (You Only Look Once) architecture to detect and recognize football field landmarks with high speed and robustness. This contribution bridges the gap between advanced neural network techniques and practical sports technology, enabling automated analysis of field geometry and player positioning. While his citation count is modest—with his top paper garnering 5 citations—his work demonstrates a clear commitment to solving real-world problems through efficient, deployable AI systems. Dwijayanto’s research is particularly valuable for students and engineers interested in the intersection of deep learning, real-time processing, and domain-specific applications like sports. His approach highlights the potential of lightweight neural networks for resource-constrained environments, making his findings relevant for both academic study and industry implementation in automated sports broadcasting, training tools, and referee assistance systems.