Papers

8

Total Citations

68

H-Index

5

About

Vladimir Golovko’s research lies at the intersection of artificial intelligence, robotics, and human-like visual perception. His most influential work centers on developing bio-inspired vision systems that mimic human eye fixation and saliency mechanisms, enabling robots to perceive and prioritize visual information in complex, dynamic environments. A standout contribution is his 2017 paper on a human-like visual-attention system for wildland firefighting assistance (21 citations), which demonstrates how AI can enhance situational awareness in hazardous settings. Golovko has also advanced multi-agent reinforcement learning for mobile robot control (16 citations), decomposing robot platforms into independently trained driving modules for more efficient navigation. His work extends to sport activity recognition using artificial neural networks (7 citations) and infrared sensor data correction for map construction (6 citations). By bridging computational models of human attention with practical robotic applications, Golovko has laid groundwork for more intuitive, autonomous systems capable of operating in unstructured environments—from factory floors to forest fires.

Research Focus

Key Achievements

5
H-Index
8
Papers
68
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
A human-like visual-attention-based artificial vision system for wildland firefighting assistance
21 citations · 2017
📈 Most Prolific Year: 2017 (2 Papers)
🤝 Key Collaborators: 22
🏛 Institutions: Brest State Technical University, Akademia Bialska im. Jana Pawła II

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago