Handwriting recognition is a classic machine learning challenge within Optical Character Recognition (OCR). It has seen substantial advancements over the years, notably with Yann LeCun’s 1998 LeNet-5 ...

Researchers proposed a deep learning-based dyslexia detection system (DDS ... Integrating YOLO’s effectiveness in object identification and MobileNet V2’s lightweight architecture enables ... Ahlawat ...

An experimental computing system physically modeled after the biological brain "learned" to identify handwritten numbers with an overall accuracy of 93.4%. The key innovation in the experiment was ...

In this project, I built a model to perform handwritten digit string recognition using synthetic data generated by concatenating digits from the MNIST dataset. Different overlapping rates and paddings ...

Automatic handwriting recognition systems are of interest for academic research fields and for commercial applications. Recent advances in deep learning techniques have shown dramatic improvement in ...

This is a MATLAB implementation of a 2 hidden-layers neural network that recognizes handwritten digit with 97% accuracy on MNIST database. The architecture and training parameters of the network is ...