Dmitriy Levonevskiy
St. Petersburg Institute for Informatics and Automation, Russian Academy of Sciences
Papers
3
Total Citations
9
H-Index
2
About
Dmitriy Levonevskiy is a researcher whose work sits at the intersection of intelligent systems, computer vision, and applied automation. His primary research areas include deep learning for facial recognition, anomaly detection in smart environments, and the integration of cloud technologies for cyber-physical systems. Levonevskiy’s most cited work, "Fast Face Features Extraction Based on Deep Neural Networks for Mobile Robotic Platforms" (2020, 4 citations), addresses the critical challenge of real-time, on-device facial processing for resource-constrained robots, contributing to more responsive and autonomous human-machine interaction. He further explores security in "Complex User Identification and Behavior Anomaly Detection in Corporate Smart Spaces" (2022, 3 citations), proposing methods to enhance safety in increasingly digitized workplaces. His notable contribution, "Software Architecture of an Automated Greenhouse Complex based on Cloud Technologies" (2021, 2 citations), tackles the urgent need for scalable, remote monitoring in precision agriculture, designing a cloud-based framework to maintain optimal microclimatic conditions for crop growth. Though early in his citation impact, Levonevskiy’s work demonstrates a clear trajectory: applying deep learning and distributed architectures to solve practical, real-world problems in robotics, security, and sustainable agriculture.
Research Focus
Key Achievements
Top Papers
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