Mustafa Albahrani

Papers

Total Citations

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About

Mustafa Albahrani is a researcher at the forefront of applied artificial intelligence and robotics, with a particular focus on integrating deep learning with autonomous systems. His most notable work, "CNN-Based Alphabet Identification and Sorting Robotic Arm" (2021), demonstrates a practical fusion of computer vision and robotic manipulation, where a convolutional neural network enables a robotic arm to identify and sort alphabet characters in real time. This contribution, while early in its citation impact with 4 citations, signals a promising direction for intelligent automation in educational and industrial sorting tasks. Albahrani’s research addresses the critical challenge of bridging perception and action in robotics, leveraging CNNs to enhance object recognition and manipulation accuracy. His work is especially relevant for students and researchers exploring low-cost, scalable solutions for automated sorting systems. By combining machine learning with hardware control, Albahrani contributes to the growing field of embodied AI, where robots learn to interact with unstructured environments. As his citation footprint grows, his foundational study serves as a stepping stone for future innovations in robotic perception and task-specific automation.