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Postal Automation System in Gurmukhi Script using Deep Learning.
- Source :
- International Journal of Image & Graphics; Jan2023, Vol. 23 Issue 1, p1-30, 30p
- Publication Year :
- 2023
-
Abstract
- Nowadays in the era of automation, the postal automation system is one of the major research areas. Developing a postal automation system for a nation like India is much troublesome than other nations because of India's multi-script and multi-lingual behavior. This proposed work will be helpful in the postal automation of district names of Punjab (state) written in Gurmukhi script, which is the official language of the state in North India. For this, a holistic approach i.e. a segmentation-free technique has been used with the help of Convolutional Neural Network (CNN) and Deep learning (DL). For the purpose of recognition, a database of 22 000 images (samples) which are handwritten in Gurmukhi script for all the 22 districts of Punjab is prepared. Each sample is written two times by 500 different writers generating 1000 samples for each district name. Two CNN models are proposed which are named as ConvNetGuru and ConvNetGuruMod for the purpose of recognition. Maximum validation accuracy achieved by ConvNetGuru is 90% and ConvNetGuruMod is 98%. [ABSTRACT FROM AUTHOR]
- Subjects :
- DEEP learning
CONVOLUTIONAL neural networks
AUTOMATION
SCRIPTS
LANGUAGE policy
Subjects
Details
- Language :
- English
- ISSN :
- 02194678
- Volume :
- 23
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- International Journal of Image & Graphics
- Publication Type :
- Academic Journal
- Accession number :
- 161586787
- Full Text :
- https://doi.org/10.1142/S0219467823500055