KHDR: Kannada Handwritten Digit Recognition Using PCA and SVM Classifier-Reference-Cited by-同舟云学术

KHDR: Kannada Handwritten Digit Recognition Using PCA and SVM Classifier

Published:2022 Issue: Volume: Page:205-214
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:
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Author:

Ramesh G,Prasanna G. B.,Santosh V. Bhat,Chandrashekar Naik,Champa H. N.

Publisher

Springer Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-4807-6_20

Reference7 articles.

1. Kunte, R.R., Samuel, F.: 170 wavelet features based on-line recognition of handwritten. J. Vis. Soc. Jpn. 20(1), 417–470 (2000)

2. Rajput, G., Rajeswari, H., Sidramappa, F.: Printed and handwritten Kannada numeral recognition using crack codes and Fourier descriptors plate. Int. J. Comput. Appl. (IJCA) Recent Trends Image Process. Pattern Recogn. (RTIPPR) 5, 3–58 (2010)

3. Chiang, C.-C., Wang, R.-H., Chen, B.-R.: Recognizing arbitrarily connected and superimposed handwritten numerals in intangible writing interfaces. Pattern Recogn. Elsevier 61, 15–28 (2017)

4. Ramappa, M.H., Krishnamurthy, S.: A comparative study of different feature extraction and classification methods for recognition of handwritten Kannada numerals. Int. J. Database Theory Appl. 6(4), 71–90 (2013)

5. Dhandra, B.V., Mukarambi, G., Hangarge, M.: Zone based features for handwritten and printed mixed kannada digits recognition. In: IJCA Proceedings on International Conference on VLSI, Communications and Instrumentation (ICVCI), vol. 7, pp. 5–8 (2011)

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