Amin Alqudah
Papers
1
Total Citations
22
H-Index
1
About
Dr. Amin Alqudah is a leading researcher in artificial intelligence, computer vision, and pattern recognition, with a particular focus on handwriting recognition and automated classification systems. His most influential work, "Recognition of Handwritten Arabic and Hindi Numerals Using Convolutional Neural Networks" (2021, 22 citations), addresses a critical challenge in automation research—the accurate detection and classification of handwritten numerals, which has broad applications in banking, postal services, and document digitization. By leveraging deep learning architectures, Dr. Alqudah has advanced the state of the art in recognizing complex, cursive scripts, making significant strides toward more robust and culturally inclusive automated systems. His contributions have been widely recognized, with his work serving as a foundational reference for subsequent studies in the field. Dr. Alqudah’s research not only enhances the efficiency of real-world applications but also pushes the boundaries of how neural networks can be tailored for non-Latin scripts, underscoring his impact on both theoretical and applied AI.
Research Focus
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Top Papers
- 1