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Review Article
Identifying Handwritten Recognition Using Logistic Regression in Pytorch
Chaithanya H1
Sai Sumanth C2
Thrisha N3
1 2 3 Department of CSE - Data Science, Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India.
Published Online: May-August 2025
Pages: 371-374
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20250402051
References
1. Hazan H, Saunders DJ, Khan H, Patel D, Sanghavi DT, Siegelmann HT, Kozma R. BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python. Front Neuroinform. 2018 Dec 12;12:89. doi: 10.3389/fninf.2018.00089. PMID: 30631269; PMCID: PMC6315182.
2. Choi, Hangseo & Jeong, Jongpil & Lee, Chaegyu & Yun, Seokwoo & Bang, Kyunga & Byun, Jaebeom. (2023). Design and Implementation for BIC Code Recognition System of Containers using OCR and CRAFT in Smart Logistics. WSEAS TRANSACTIONS ON COMPUTER RESEARCH. 11. 62-72. 10.37394/232018.2023.11.6.
3. Liman, Muhamad & Josef, Antonio. (2024). Handwritten Character Recognition using Deep Learning Algorithm with Machine Learning Classifier. JOIV: International Journal on Informatics Visualization. 8. 10.62527/joiv.8.1.1707.
4. C. C. Tappert, C. Y. Suen and T. Wakahara, "The state of the art in online handwriting recognition," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 8, pp. 787-808, Aug. 1990, doi: 10.1109/34.57669.
5. T. Akter, M. S. Akter, T. Mahmud, R. Chakma, M. S. Hossain and K. Andersson, "Evaluating the Performance of Machine Learning Models in Handwritten Signature Verification," 2024 Asia Pacific Conference on Innovation in Technology (APCIT), MYSORE, India, 2024, pp. 1-6, doi: 10.1109/APCIT62007.2024.10673648.
6. Anna Agius, Marie Morelato, Sébastien Moret, Scott Chadwick, Kylie Jones, Rochelle Epple, James Brown, Claude Roux,Dataset of coded handwriting features for use in statistical modelling,Data in Brief,Volume 16,2018,Pages 1010-1024,ISSN 2352 3409
7. Shah, Faisal & Kamran, Yousaf. (2007). Handwritten Digit Recognition Using Image Processing and Neural Networks. Lecture Notes in Engineering and Computer Science. 2165.
8. Millán-Hernández, Christian Eduardo & García Hernández, René Arnulfo & Ledeneva, Yulia. (2019). An evolutionary logistic regression method to identify confused drug names. Journal of Intelligent & Fuzzy Systems. 36. 1-11. 10.3233/JIFS-179012.
9. J. Li, G. Sun, L. Yi, Q. Cao, F. Liang and Y. Sun, "Handwritten Digit Recognition System Based on Convolutional Neural Network," 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications( AEECA), Dalian, China, 2020, pp. 739-742, doi: 10.1109/AEECA49918.2020.9213619.
10. Alejandro Baldominos, Yago Saez, Pedro Isasi,Evolutionary convolutional neural networks: An application to handwriting recognition,Neurocomputing,Volume 283,2018,Pages 38-52,ISSN 0925-231
2. Choi, Hangseo & Jeong, Jongpil & Lee, Chaegyu & Yun, Seokwoo & Bang, Kyunga & Byun, Jaebeom. (2023). Design and Implementation for BIC Code Recognition System of Containers using OCR and CRAFT in Smart Logistics. WSEAS TRANSACTIONS ON COMPUTER RESEARCH. 11. 62-72. 10.37394/232018.2023.11.6.
3. Liman, Muhamad & Josef, Antonio. (2024). Handwritten Character Recognition using Deep Learning Algorithm with Machine Learning Classifier. JOIV: International Journal on Informatics Visualization. 8. 10.62527/joiv.8.1.1707.
4. C. C. Tappert, C. Y. Suen and T. Wakahara, "The state of the art in online handwriting recognition," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, no. 8, pp. 787-808, Aug. 1990, doi: 10.1109/34.57669.
5. T. Akter, M. S. Akter, T. Mahmud, R. Chakma, M. S. Hossain and K. Andersson, "Evaluating the Performance of Machine Learning Models in Handwritten Signature Verification," 2024 Asia Pacific Conference on Innovation in Technology (APCIT), MYSORE, India, 2024, pp. 1-6, doi: 10.1109/APCIT62007.2024.10673648.
6. Anna Agius, Marie Morelato, Sébastien Moret, Scott Chadwick, Kylie Jones, Rochelle Epple, James Brown, Claude Roux,Dataset of coded handwriting features for use in statistical modelling,Data in Brief,Volume 16,2018,Pages 1010-1024,ISSN 2352 3409
7. Shah, Faisal & Kamran, Yousaf. (2007). Handwritten Digit Recognition Using Image Processing and Neural Networks. Lecture Notes in Engineering and Computer Science. 2165.
8. Millán-Hernández, Christian Eduardo & García Hernández, René Arnulfo & Ledeneva, Yulia. (2019). An evolutionary logistic regression method to identify confused drug names. Journal of Intelligent & Fuzzy Systems. 36. 1-11. 10.3233/JIFS-179012.
9. J. Li, G. Sun, L. Yi, Q. Cao, F. Liang and Y. Sun, "Handwritten Digit Recognition System Based on Convolutional Neural Network," 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications( AEECA), Dalian, China, 2020, pp. 739-742, doi: 10.1109/AEECA49918.2020.9213619.
10. Alejandro Baldominos, Yago Saez, Pedro Isasi,Evolutionary convolutional neural networks: An application to handwriting recognition,Neurocomputing,Volume 283,2018,Pages 38-52,ISSN 0925-231
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