Ghazanfar Latif
Papers
1
Total Citations
4
H-Index
1
About
Dr. Ghazanfar Latif is a researcher whose work sits at the intersection of robotics, computer vision, and applied deep learning. His most cited paper, "CNN-Based Alphabet Identification and Sorting Robotic Arm" (2021), with 4 citations, demonstrates a practical integration of convolutional neural networks with physical automation. This contribution showcases his ability to bridge algorithmic innovation with real-world robotic manipulation, offering a tangible solution for automated sorting and identification tasks. While his citation count is currently modest, his research signals a focused interest in deploying AI for precise, sensor-driven control systems. Dr. Latif’s work is particularly relevant for students and engineers exploring how deep learning can enhance robotic perception and decision-making in industrial or educational settings. His approach—combining CNN-based visual recognition with mechanical actuation—lays groundwork for more adaptive and intelligent automation systems.
Research Focus
Key Achievements
Top Papers
- 1CNN-Based Alphabet Identification and Sorting Robotic Arm4 citations · 2021