Vadim Lukyanov

Bauman Moscow State Technical University

Papers

Total Citations

H-Index

About

Vadim Lukyanov is a researcher advancing the field of computer vision, with a particular focus on real-time object detection and surveillance systems. His most cited work, "Moving Person Detection Based on Modified YOLOv5" (2023), demonstrates his expertise in enhancing deep learning architectures for practical applications. By adapting the YOLOv5 framework, Lukyanov improved the accuracy and efficiency of detecting moving individuals in dynamic environments—a critical capability for security, autonomous systems, and human-robot interaction. While his citation count is still growing, this paper reflects his commitment to solving real-world challenges through algorithmic refinement. Lukyanov’s contributions lie at the intersection of neural network optimization and applied machine learning, offering scalable solutions for video analytics. His work is particularly relevant for researchers and engineers developing robust detection systems in cluttered or high-traffic scenarios. As his research continues to evolve, Lukyanov is poised to make further strides in making computer vision systems more responsive and reliable.