• Dr. Preeti Baser
• Jui Khamar

In recent years, handwritten character recognition has been an important area due to its applications in several fields. This paper proposes a methodology to recognize handwritten character for the Gujarati language using convolutional neural network. Gujarati character recognition that faces several challenges, including unlimited variation in human handwriting styles. Although such a network can be used as unified framework for both feature extraction and classification, it is more efficient as a feature extractor than as a classifier. This paper suggests how a deep learning technique can be effectively applied to recognize Gujarati handwritten characters.

Convolutional Neural Network (CNN), Feature Extraction, Max pooling, Softmax

"A Novel Approach to Classify Gujarati Handwritten Characters Using Convolutional Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.110-114, June 2019, Available :http://www.jetir.org/papers/JETIR1906R54.pdf

"A Novel Approach to Classify Gujarati Handwritten Characters Using Convolutional Neural Network", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp110-114, June 2019, Available at : http://www.jetir.org/papers/JETIR1906R54.pdf