Shahid Karim
Papers
1
Total Citations
13
H-Index
1
About
Shahid Karim is a researcher at the forefront of applying deep learning to agricultural robotics and computer vision. His work focuses on developing intelligent systems that can identify and classify crops and their components—such as chili plants and their flowers—to enable automated harvesting and precision farming. In his most cited study, "Classification and detection of chili and its flower using deep learning approach" (2020, 13 citations), Karim introduced a Deep Neural Network (DNN)-based detector tailored for a local chili variety, addressing a critical bottleneck in robotic vision for selective picking. This contribution not only advances the field of agricultural automation but also demonstrates how deep learning can be adapted to specific, real-world cultivation challenges. By bridging the gap between computer vision algorithms and practical farming needs, Karim’s work has laid the groundwork for more efficient, labor-saving technologies in horticulture. His research is particularly valuable for students and engineers interested in the intersection of AI, robotics, and sustainable agriculture, showing how targeted deep learning solutions can transform traditional farming practices.
Research Focus
Key Achievements
Top Papers
- 1