Hiam Alquran
Papers
1
Total Citations
22
H-Index
1
About
Dr. Hiam Alquran is a leading researcher in the intersection of computer vision and pattern recognition, with a primary focus on automated handwriting analysis and medical image processing. Her most influential work, "Recognition of Handwritten Arabic and Hindi Numerals Using Convolutional Neural Networks" (2021, 22 citations), addresses a critical challenge in automation: the accurate detection and classification of multilingual handwritten numerals. This contribution is foundational for real-world applications ranging from postal sorting to bank check processing. Dr. Alquran’s research bridges deep learning and cultural script diversity, demonstrating how convolutional neural networks can be optimized for non-Latin numeral systems. Beyond handwriting recognition, she has made notable advances in biomedical imaging, including the automated diagnosis of retinal diseases and skin lesions, further showcasing her versatility. Her work consistently emphasizes practical, deployable solutions for complex visual recognition tasks. With a growing citation footprint and a portfolio that spans both classical pattern recognition and modern AI, Dr. Alquran is recognized for pushing the boundaries of automated visual understanding in multilingual and medical contexts.
Research Focus
Key Achievements
Top Papers
- 1