Papers
1
Total Citations
2
H-Index
1
About
R. E. Glushankov is a researcher at the intersection of artificial intelligence and agricultural science, with a primary focus on applying deep learning to phytosanitary monitoring. His most notable contribution is the development of a convolutional neural network model for automated disease detection in fruit crops, specifically apple trees, using the YOLOv10-X architecture with transfer learning. This work, published in 2025, demonstrates how advanced computer vision can classify diseases from leaf and fruit images, offering a scalable, real-time solution for precision agriculture. Though early in its citation impact, the study represents a significant step toward integrating neural networks into crop management systems, potentially reducing reliance on manual inspection and chemical treatments. Glushankov’s research bridges the gap between cutting-edge AI techniques and practical agricultural challenges, positioning him as an emerging voice in smart farming. His work not only advances phytosanitary monitoring but also highlights the transformative role of deep learning in sustainable agriculture, making it a valuable reference for researchers exploring AI-driven environmental and food security solutions.
Research Focus
Key Achievements
Top Papers
- 1