Hassan Ghaziri
Papers
1
Total Citations
17
H-Index
1
About
Hassan Ghaziri is a researcher whose work sits at the intersection of machine learning, humanitarian technology, and signal processing. His most cited contribution, “Detection and classification of landmines using machine learning applied to metal detector data” (2020, 17 citations), addresses a critical global challenge: the high false-alarm rates that plague manual landmine clearance. By applying machine learning to metal detector signals, Ghaziri’s work offers a path toward more reliable, automated discrimination between actual landmines and harmless clutter—a development with profound implications for demining safety and efficiency. This research exemplifies his focus on translating computational methods into real-world, life-saving applications. While his citation count is still growing, the practical and humanitarian weight of his contributions is significant. Ghaziri’s work is particularly notable for its potential to reduce the risks faced by deminers and to accelerate the clearance of contaminated land, making him a promising voice in the field of applied machine learning for social impact.
Research Focus
Key Achievements
Top Papers
- 1