Christos Klaridopoulos
Papers
2
Total Citations
12
H-Index
2
About
Christos Klaridopoulos is a rising researcher at the forefront of precision agriculture, specializing in the fusion of artificial intelligence and molecular biology for early plant disease detection. His work centers on developing non-invasive, AI-driven diagnostic tools to combat devastating fungal pathogens, particularly *Botrytis cinerea*, the causal agent of grey mould. Klaridopoulos’s major contributions include pioneering the use of multi-spectral imaging combined with transformer-based deep learning architectures, as demonstrated in his 2024 paper on tomato grey mould detection. He has also conducted critical comparative evaluations of AI-based imaging against PCR-based molecular assays, validating the efficacy of optical sensing for real-time, field-deployable diagnostics on crops like pepper. His research directly addresses the challenge of equipping autonomous agricultural robots with reliable early-warning systems. With over 12 citations across his most recent works, Klaridopoulos is establishing a strong impact in the agri-tech community. His notable achievement lies in bridging the gap between computational vision and plant pathology, offering scalable solutions that promise to reduce crop losses and enhance global food security.
Research Focus
Key Achievements
Top Papers
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