Handwritten Digit Recognition Using Probabilistic Neural Networks
Handwritten character recognition falls within the domain of optical character recognition, employing probabilistic neural networks as classifiers to categorize handwritten digits represented as binary images. The resulting classifier achieves 100% accuracy on training samples, with implementation involving feature extraction and pattern layer optimization.