Praveen Kumar Sekharamantry
Papers
1
Total Citations
67
H-Index
1
About
Praveen Kumar Sekharamantry is a researcher at the forefront of applying deep learning to precision agriculture, with a particular focus on automating fruit detection and harvesting. His most cited work, "Deep Learning-Based Apple Detection with Attention Module and Improved Loss Function in YOLO" (2023, 67 citations), addresses a critical challenge in modern horticulture: enabling machines to accurately identify apples in complex orchard environments. By integrating attention mechanisms and refining loss functions within the YOLO architecture, Sekharamantry’s approach significantly boosts detection accuracy, a vital step toward fully autonomous farming systems. His research directly supports Italy’s robust apple industry, demonstrating how AI can enhance efficiency and reduce labor dependency in agriculture. With a growing citation impact, Sekharamantry’s contributions exemplify the practical fusion of computer vision and agronomy, offering scalable solutions for crop monitoring and yield estimation. His work not only advances smart farming technologies but also inspires further innovation in deep learning applications for agricultural automation.
Research Focus
Key Achievements
Top Papers
- 1