This work deals with a case study of automatic recognition of handwritten documents, embracing techniques and algorithms from both qualitative and quantitative sides. The challenge of the handwritten ...

This work deals with a case study of automatic recognition of handwritten documents, embracing techniques and algorithms from both qualitative and quantitative sides. The challenge of the handwritten ...

This repository focuses on handwritten digit recognition using the MNIST dataset. It includes implementations of Logistic Regression, MLP, and LeNet-5 in PyTorch, organized into folders for reports, ...

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 ...

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 ...

One of the capabilities of deep learning is image recognition, The “hello world” of object recognition for machine learning and deep learning is the MNIST dataset for handwritten digit recognition.