Handwritten Character Recognition
Abstract
The purpose of this task is to review existing handwritten character recognition methods using machine learning algorithms and implement improved accurate and effectual methods. Here is deep learning neural network to recognize handwritten text. Thanks to the data pipeline, we were capable to create our own dataset and apply deep learning to character recognition. This function prototype can detect handwritten characters from images scanned using a neural network.
How to cite this article:
Vashistha S, Mishra S, Bhayana D. Handwritten Character Recognition. J Adv Res Electro Engi Tech 2020; 7(2):1-4.
References
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[2]. R. Plamondon et al., "On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, 2000.
[3]. K. Simonyan, A. Zisserman, "Very Deep Convolutional Networks for Large-Scale Image Recognition arXiv technical report", 2014
[4]. Shaoqing Ren, Kaiming He, Ross Girshick, Jian Sun. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks. Neural Information Processing Systems (NIPS), 2015
[5]. M. Merler, C. Galleguillos, and S. Belongie. Recognizing groceries in situ using in vitro training data. In SLAM, 2007.
[6]. J. J. Weinman, E. Learned-Miller, and A. R. Hanson. Scene text recognition using similarity and a lexicon with sparse belief propagation. IEEE TPAMI, 31:1733–1746, 2009
Published
2021-06-03
How to Cite
VASHISTHA, Sudhanshu; MISHRA, Shilpi; BHAYANA, Dipti.
Handwritten Character Recognition.
Journal of Advanced Research in Electronics Engineering and Technology, [S.l.], v. 7, n. 2, p. 1-4, june 2021.
ISSN 2456-1428.
Available at: <http://thejournalshouse.com/index.php/electronics-engg-technology-adr/article/view/146>. Date accessed: 22 jan. 2025.
Section
Articles
