🧠 Handwritten Digit Recognition using Deep Learning This project implements a CNN-based image classification model using the MNIST dataset to recognize handwritten digits from 0 to 9. It is built ...

Handwritten Mathematical Expression Recognition Publication Trend The graph below shows the total number of publications each year in Handwritten Mathematical Expression Recognition.

Computer science and having to deal with written documents by hand are the most important issues when considering digitising data that is written manually. This work deals with a case study of ...

Renderform is a handwritten mathematical formula recognition system that processes images of handwritten text and parses them into recognized mathematical formulas, which can be rendered in LaTeX. The ...

Citation: Vallejo-Mancero B, Madrenas J and Zapata M (2024) Real-time execution of SNN models with synaptic plasticity for handwritten digit recognition on SIMD hardware.

Never before have people relied so much on technology; now, machine learning and based on machine learning can do anything from classifying objects in photos to inserting sounds to old movies. Similar ...

Keywords: spiking neural network, STDP, unsupervised learning, classification, digit recognition Citation: Diehl PU and Cook M (2015) Unsupervised learning of digit recognition using ...

We demonstrate this idea computationally using competitive learning networks for recognizing handwritten digits. Animations of the learning process show how training the network with patterns from an ...