Authors :
A.Leela Vathi; V.Jyothsna Rani; A.Devi Siva Prasad; S.Sai Nikitha; D.Vijaya Lakshmi; K.Renuka
Volume/Issue :
Volume 8 - 2023, Issue 12 - December
Google Scholar :
https://tinyurl.com/4ntn7mjb
Scribd :
https://tinyurl.com/5n7n2ndn
DOI :
https://doi.org/10.5281/zenodo.10405523
Abstract :
Due to the variations in human handwriting,
computerized handwritten digit recognition is a
challenging task. This abstract describes a system that
identifies handwritten digits in images and documents
using Convolutional Neural Networks built with
PyTorch. In order to solve a variety of practical
problems, this technology is crucial in applications like
check processing, postal sorting, and number plate
recognition. The abstract compares different machine
learning and deep learning algorithms, such as Support
Vector Machine, Multilayer Perceptron, and
Convolutional Neural Network, based on their
performance, accuracy, and training times. The results
are presented visually for easy comprehension through
Matplotlib-generated plots and charts, providing
insightful information into the state of handwritten digit
recognition and opening the door for improvements in
this crucial area of artistic endeavor.
Keywords :
Deep Learning, Convolutional Neural Network(CNN), Support Vector Machine(SVM),MINIST Dataset.
Due to the variations in human handwriting,
computerized handwritten digit recognition is a
challenging task. This abstract describes a system that
identifies handwritten digits in images and documents
using Convolutional Neural Networks built with
PyTorch. In order to solve a variety of practical
problems, this technology is crucial in applications like
check processing, postal sorting, and number plate
recognition. The abstract compares different machine
learning and deep learning algorithms, such as Support
Vector Machine, Multilayer Perceptron, and
Convolutional Neural Network, based on their
performance, accuracy, and training times. The results
are presented visually for easy comprehension through
Matplotlib-generated plots and charts, providing
insightful information into the state of handwritten digit
recognition and opening the door for improvements in
this crucial area of artistic endeavor.
Keywords :
Deep Learning, Convolutional Neural Network(CNN), Support Vector Machine(SVM),MINIST Dataset.
