Sijan Karki
Papers
2
Total Citations
22
H-Index
2
About
Sijan Karki is a researcher at the forefront of agricultural robotics, specializing in computer vision and deep learning for precision harvesting. His work focuses on developing lightweight, high-accuracy detection algorithms to enable robotic systems to autonomously identify and harvest delicate fruits like strawberries. Karki’s major contributions include the creation of the "Lightweight Improved YOLOv5s-CGhostnet," a novel algorithm that balances speed and robustness for real-time strawberry maturity level detection and counting, achieving 15 citations. This work addresses critical challenges in deploying efficient models on resource-constrained harvesting robots. Additionally, his research on "Peduncle Detection of Ripe Strawberry to Localize Picking Point Using DF-Mask R-CNN and Monocular Depth" (7 citations) provides a sophisticated solution for accurate picking point localization and depth estimation, essential for bruise-free harvesting by grasping the peduncle. Together, these contributions advance the practical implementation of robotic harvesting systems, reducing fruit damage and improving efficiency. Karki’s work is notable for its direct application to agricultural automation, offering scalable solutions that integrate cutting-edge vision models with real-world robotic constraints.
Research Focus
Key Achievements
Top Papers
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