Muhammad Adnan Khalil
Scuola Superiore Sant'Anna, National University of Sciences and Technology
Papers
2
Total Citations
26
H-Index
2
About
Muhammad Adnan Khalil is a researcher specializing in computer vision, deep learning, and embedded systems, with a strong focus on real-world automation and safety. His work bridges artificial intelligence and industrial applications, particularly in quality assurance and robotics. In his highly cited 2023 paper, Khalil developed a deep convolutional neural network for contamination detection in food and medical packaging, addressing a critical need for hygienic, automated quality control. This work has already garnered 17 citations, reflecting its relevance to both industry and academia. Earlier, Khalil contributed to robotics with a 2018 study on ball detection and tracking using image processing on embedded systems, achieving robust object recognition in complex scenes—a foundational challenge in autonomous systems. His research demonstrates a commitment to deploying intelligent, efficient solutions that enhance machine-environment interaction. By integrating deep learning with practical constraints like real-time processing and safety, Khalil’s work offers valuable insights for students and engineers developing next-generation automated inspection and robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2