Abolghasem Shahbazi

North Carolina Agricultural and Technical State University

Papers

1

Total Citations

52

H-Index

1

About

Dr. Abolghasem Shahbazi is a leading researcher at the intersection of precision agriculture and artificial intelligence, with a primary focus on leveraging advanced sensing and computational techniques to enhance crop management and environmental sustainability. His most cited work, "Deep Convolutional Neural Networks for Weeds and Crops Discrimination From UAS Imagery" (2022, 52 citations), exemplifies his major contribution: developing deep learning models that analyze unmanned aerial system (UAS) imagery to accurately distinguish between weeds and crops. This innovation directly addresses the critical challenge of reducing excessive herbicide use, which can harm ecosystems and human health. By enabling targeted weed control, Dr. Shahbazi’s research promotes more efficient, eco-friendly farming practices. His work has significant implications for precision agriculture, offering scalable solutions to improve crop yield and quality while minimizing environmental impact. Beyond this flagship study, his broader research portfolio encompasses remote sensing, machine learning, and sustainable agricultural systems, earning him recognition as a key innovator in applying AI to real-world agricultural problems. His findings are widely cited by scholars and practitioners aiming to integrate smart technologies into modern farming, solidifying his influence in the field.

Research Focus

Key Achievements

1
H-Index
1
Papers
52
Total Citations
52
Avg Citations/Paper
🏆 Most Cited Paper
Deep Convolutional Neural Networks for Weeds and Crops Discrimination From UAS Imagery
52 citations · 2022
📈 Most Prolific Year: 2022 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: North Carolina Agricultural and Technical State University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago