- Research Article
- 10.15662/ijeetr.2026.0802008
Handwritten Character Recognition Using Neural Networks
- Mar 18, 2026
- International Journal of Engineering & Extended Technologies Research
- K Prasad + 7 more +7
In the c formation and automation, efficient ai.d accurate text recognition plays a crucial role in bridging the gap between human writing and comp riting and compu, interpretation. Our project, the Handwritten Character Recognition (HCR) System using leural Networks, addresses this need by establishing an intelligent model capable of identifying and classifying handwi racter with high precision. The system utilizes deep learning techniques, specifically Convolutional Neurai Networks (CNNs), to analyze handwritten input images and cotvert them into machine-readable text. Built on a scalab t neural network architecture, this system employs advanced prepro- cessing methods su nage normalization, noise reduction, and segmentation to ensure accurate recognition. The crained using a large set of handwritien samples, enabling the model to learn diverse writing styles and patterns. The The trained model then predicts the corresponding characters with improved accuracy through multiple feature extre tion and classification layers.
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