V. A. Abrosimov
Papers
1
Total Citations
5
H-Index
1
About
V. A. Abrosimov is a researcher whose work sits at the intersection of computer vision, deep learning, and mobile robotics. His primary research focus is the application of advanced neural network architectures—specifically deep convolutional neural networks (CNNs)—to solve real-world problems in visual navigation and object recognition. In his most cited work, "Application of algorithms for object recognition based on deep convolutional neural networks for visual navigation of a mobile robot" (2018), Abrosimov provides a critical analysis of state-of-the-art CNN-based approaches, evaluating their feasibility for deployment in autonomous robotic systems. This review has garnered 5 citations, serving as a practical guide for researchers integrating AI-driven perception into mobile platforms. By bridging the gap between theoretical deep learning models and applied robotics, Abrosimov’s contributions help advance the development of more intelligent, visually-guided autonomous agents. His work is particularly valuable for students and engineers seeking to understand how cutting-edge object recognition algorithms can be adapted for real-time navigation tasks in dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1