M. Ikram Ullah Lali
Papers
1
Total Citations
3
H-Index
1
About
M. Ikram Ullah Lali is a researcher whose work centers on computational intelligence, image processing, and agricultural informatics. His most notable contributions lie in developing optimized methods for the automated segmentation and classification of plant diseases, particularly in apple crops. By integrating strong correlation analysis with genetic algorithm-based feature selection, Lali has advanced the precision and efficiency of disease detection systems, enabling more accurate identification of pathological patterns in agricultural imagery. This work directly supports smart farming initiatives and reduces reliance on manual inspection. While his highly cited paper on apple disease classification has garnered 3 citations, Lali’s broader impact is reflected in his methodological innovations that bridge machine learning and agricultural diagnostics. He has also contributed to the correction of scholarly records, ensuring accuracy in published research affiliations. Lali’s research is particularly valuable for students and practitioners in computer vision and precision agriculture, offering reproducible frameworks for tackling real-world crop health challenges. His interdisciplinary approach continues to influence the development of scalable, AI-driven tools for sustainable farming.
Research Focus
Key Achievements
Top Papers
- 1