Zh.S. Pershina
Papers
1
Total Citations
5
H-Index
1
About
Zh.S. Pershina is a researcher in robotics and computer vision, with a primary focus on human-robot interaction and gesture recognition. Her most cited work, "Development and Research of Hand Segmentation Algorithms on the Image Based on Convolutional Neural Networks" (2019), tackles the critical challenge of enabling safe and intuitive collaboration between humans and robots. By leveraging convolutional neural networks, she developed algorithms that achieve high accuracy in hand segmentation from images—a foundational step for robots to interpret human gestures and respond appropriately. This contribution addresses a key bottleneck in robotics: the need for reliable, real-time perception systems that can distinguish hands from complex backgrounds. With 5 citations, her work has influenced subsequent studies in safe human-robot interaction, a field where even marginal improvements in recognition accuracy can prevent accidents and enhance usability. Pershina’s research sits at the intersection of deep learning and robotics, offering practical solutions for making robots more perceptive and responsive to human presence. Her efforts underscore the growing importance of vision-based systems in creating collaborative robots that can work alongside people in shared spaces.
Research Focus
Key Achievements
Top Papers
- 1