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A Transfer Learning Approach for Handwritten Numeral Digit Recognition

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Le ZhangAuthors Info & Claims

ICSIM '20: Proceedings of the 3rd International Conference on Software Engineering and Information Management

Pages 140 - 145

https://doi.org/10.1145/3378936.3378970

Published: 07 March 2020 Publication History

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Abstract

Handwritten numeral digit recognition is a classical problem in the field of computer vision, which has a wide range of applications in various fields including financial and post services. The accuracy of handwritten numeral digit recognition has been greatly improved by using deep learning in the past few years. However, deep learning relies on a large amount of training data and time-consuming calculation. In this paper, we adopt a transfer learning approach for handwritten numeral digit recognition and use both the multi-layer perceptron and convolutional neural network models to share the feature extraction process among five handwritten numerical datasets, namely, Tibetan, Arabic, Bangla, Devanagari, and Telugu. We compare the transfer learning scheme with the model based on a single dataset. We find that using the transfer learning method can significantly reduce the training time of the deep learning models, and slightly reduces the recognition accuracy.

References

[1]

LeCun Y, Bottou L, Bengio Y, et al. Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998, 86(11): 2278--2324.

Crossref

Google Scholar

[2]

LeCun Y, Bengio Y, Hinton G. Deep learning[J]. nature, 2015, 521(7553): 436.

Google Scholar

[3]

Krizhevsky A, Sutskever I, Hinton G E. Imagenet classification with deep convolutional neural networks[C]//Advances in neural information processing systems. 2012: 1097--1105.

Google Scholar

[4]

Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets[C]//Advances in neural information processing systems. 2014: 2672--2680.

Google Scholar

[5]

Jiang W, Zhang L. Geospatial data to images: A deep-learning framework for traffic forecasting[J]. Tsinghua Science and Technology, 2018, 24(1): 52--64.

Crossref

Google Scholar

[6]

Hassan T, Khan H A. Handwritten bangla numeral recognition using local binary pattern[C]//2015 International Conference on Electrical Engineering and Information Communication Technology (ICEEICT). IEEE, 2015: 1--4.

Google Scholar

[7]

Sarkhel R, Das N, Saha A K, et al. A multi-objective approach towards cost effective isolated handwritten Bangla character and digit recognition[J]. Pattern Recognition, 2016, 58: 172--189.

Digital Library

Google Scholar

[8]

Bhattacharya U, Chaudhuri B B. Handwritten numeral databases of Indian scripts and multistage recognition of mixed numerals[J]. IEEE transactions on pattern analysis and machine intelligence, 2008, 31(3): 444--457.

Google Scholar

[9]

Maitra D S, Bhattacharya U, Parui S K. CNN based common approach to handwritten character recognition of multiple scripts[C]//2015 13th International Conference on Document Analysis and Recognition (ICDAR). IEEE, 2015: 1021--1025.

Google Scholar

[10]

Shopon M, Mohammed N, Abedin M A. Bangla handwritten digit recognition using autoencoder and deep convolutional neural network[C]//2016 International Workshop on Computational Intelligence (IWCI). IEEE, 2016: 64--68.

Google Scholar

[11]

Alom M Z, Sidike P, Taha T M, et al. Handwritten bangla digit recognition using deep learning[J]. arXiv preprint arXiv:1705.02680, 2017.

Google Scholar

[12]

Pramanik R, Dansena P, Bag S. A Study on the Effect of CNN-Based Transfer Learning on Handwritten Indic and Mixed Numeral Recognition[C]//Workshop on Document Analysis and Recognition. Springer, Singapore, 2018: 41--51.

Google Scholar

[13]

Zunair H, Mohammed N, Momen S. Unconventional Wisdom: A New Transfer Learning Approach Applied to Bengali Numeral Classification[C]//2018 International Conference on Bangla Speech and Language Processing (ICBSLP). IEEE, 2018: 1--6.

Google Scholar

[14]

Tushar A K, Ashiquzzaman A, Afrin A, et al. A novel transfer learning approach upon hindi, arabic, and bangla numerals using convolutional neural networks[M]//Computational Vision and Bio Inspired Computing. Springer, Cham, 2018: 972--981.

Google Scholar

Cited By

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Gayathri RBabitha Lincy R(2022)Transfer learning based handwritten character recognition of tamil script using inception-V3 ModelJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-21237842:6(6091-6102)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/JIFS-212378
Ramoliya DGoel PVaidya JVadaliya P(2022)University Indoor Scene Classification using Transfer Learning2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA)10.1109/ICIRCA54612.2022.9985516(793-797)Online publication date: 21-Sep-2022
https://doi.org/10.1109/ICIRCA54612.2022.9985516
Lanjewar VKhobragade R(2021)Transfer learning using Pre-trained AlexNet for Marathi Handwritten Compound Character Image Classification2021 International Conference on Intelligent Technologies (CONIT)10.1109/CONIT51480.2021.9498418(1-7)Online publication date: 25-Jun-2021
https://doi.org/10.1109/CONIT51480.2021.9498418
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Index Terms

A Transfer Learning Approach for Handwritten Numeral Digit Recognition
1. Applied computing
  1. Document management and text processing
    1. Document capture
      1. Optical character recognition

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Published In

ICSIM '20: Proceedings of the 3rd International Conference on Software Engineering and Information Management

January 2020

258 pages

ISBN:9781450376907

DOI:10.1145/3378936

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Science and Technology of China: University of Science and Technology of China

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 March 2020

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ICSIM '20

ICSIM '20: The 3rd International Conference on Software Engineering and Information Management

January 12 - 15, 2020

NSW, Sydney, Australia

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Cited By

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Gayathri RBabitha Lincy R(2022)Transfer learning based handwritten character recognition of tamil script using inception-V3 ModelJournal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology10.3233/JIFS-21237842:6(6091-6102)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/JIFS-212378
Ramoliya DGoel PVaidya JVadaliya P(2022)University Indoor Scene Classification using Transfer Learning2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA)10.1109/ICIRCA54612.2022.9985516(793-797)Online publication date: 21-Sep-2022
https://doi.org/10.1109/ICIRCA54612.2022.9985516
Lanjewar VKhobragade R(2021)Transfer learning using Pre-trained AlexNet for Marathi Handwritten Compound Character Image Classification2021 International Conference on Intelligent Technologies (CONIT)10.1109/CONIT51480.2021.9498418(1-7)Online publication date: 25-Jun-2021
https://doi.org/10.1109/CONIT51480.2021.9498418
Fateh AFateh MAbolghasemi V(2021)Multilingual handwritten numeral recognition using a robust deep network joint with transfer learningInformation Sciences: an International Journal10.1016/j.ins.2021.09.051581:C(479-494)Online publication date: 1-Dec-2021
https://dl.acm.org/doi/10.1016/j.ins.2021.09.051

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