M. Gopikrishnan
Papers
1
Total Citations
3
H-Index
1
About
M. Gopikrishnan is a researcher in agricultural technology and deep learning, with a focus on precision weed detection. Their most-cited work, "Design and evaluation of a deep CNN algorithm for detecting farm weeds" (2023, 3 citations), addresses a critical challenge in sustainable farming: reducing herbicide overuse and manual labor by enabling targeted weed identification. By developing a convolutional neural network (CNN) tailored for farm environments, Gopikrishnan’s research aims to improve the accuracy and efficiency of automated weed removal systems, directly contributing to environmentally friendly agriculture. Although early in their career, this work highlights a commitment to solving real-world problems at the intersection of computer vision and agronomy. Their contributions have the potential to minimize ecological harm from broad-spectrum spraying while saving time for farmers. As the field of smart agriculture grows, Gopikrishnan’s foundational algorithm offers a promising step toward scalable, AI-driven crop management.
Research Focus
Key Achievements
Top Papers
- 1Design and evaluation of a deep CNN algorithm for detecting farm weeds3 citations · 2023