Achyar Ulul Amri
Papers
1
Total Citations
3
H-Index
1
About
Achyar Ulul Amri is a researcher at the forefront of applying computer vision and artificial intelligence to agricultural challenges, with a particular focus on precision horticulture. His most cited work, "Automatic diagnosis of a multi-symptom grape vine disease using computer vision" (2023), demonstrates a novel approach to detecting and classifying complex plant diseases that present with multiple visual symptoms. This research, presented at the prestigious XXXI International Horticultural Congress (IHC2022), has already garnered 3 citations, signaling its growing influence in the field of digital agriculture. By developing automated diagnostic tools, Amri addresses a critical need for early, accurate disease detection in viticulture—a sector where timely intervention can significantly reduce crop losses and pesticide use. His work bridges the gap between advanced machine learning techniques and practical farming applications, offering scalable solutions for sustainable crop management. Amri’s contributions are particularly valuable for researchers and students exploring the intersection of computer vision, deep learning, and precision agriculture, as his methodologies provide a template for tackling similar multi-symptom disease challenges in other crops.
Research Focus
Key Achievements
Top Papers
- 1