Deep Learning for Roman Handwritten Character Recognition

Main Authors: Muhaafidz Md Saufi, Mohd Afiq Zamanhuri, Norasiah Mohammad, Zaidah Ibrahim
Format: Article Journal
Terbitan: , 2018
Subjects:
CNN
Online Access: https://zenodo.org/record/4314254
Daftar Isi:
  • The advantage of deep learning is that the analysis and learning of massive amounts of unsupervised data make it a beneficial tool for Big Data analysis. Convolution Neural Network (CNN) is a deep learning method that can be used to classify image, cluster them by similarity, and perform image recognition in the scene. This paper conducts a comparative study between three deep learning models, which are simple-CNN, AlexNet and GoogLeNet for Roman handwritten character recognition using Chars74K dataset. The produced results indicate that GooleNet achieves the best accuracy but it requires a longer time to achieve such result while AlexNet produces less accurate result but at a faster rate.