Manisha Ajmani

University of Winnipeg

Papers

1

Total Citations

31

H-Index

1

About

Manisha Ajmani is a researcher at the intersection of embedded systems and agricultural technology, with a primary focus on enabling machine learning applications for precision farming. Her most notable contribution is the development of an innovative embedded system for the automated generation of labeled plant images, directly addressing the critical bottleneck of insufficient training data in agricultural ML. This work, published in 2020 and garnering 31 citations, provides a scalable solution for creating diverse, high-quality datasets essential for training models in autonomous plant classification and other agri-tech tasks. By automating the data labeling process, Ajmani’s research significantly reduces the manual effort required to build robust ML systems, thereby accelerating the deployment of AI-driven tools in agriculture. Her work stands out for its practical, hardware-integrated approach, bridging the gap between sensor systems and computational models. Ajmani’s contributions are particularly valuable for researchers and students exploring the challenges of data scarcity in domain-specific AI applications, positioning her as a key figure in the advancement of smart farming technologies.

Research Focus

Key Achievements

1
H-Index
1
Papers
31
Total Citations
31
Avg Citations/Paper
🏆 Most Cited Paper
An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture
31 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Winnipeg

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago