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Original Article
Deep Learning Based Ahom Alphabet Recognition System Using Convolutional Neural Network
Antom Parashar1
Dr. Dhrubajyoti Baruah2
1 2 Department of Computer Application, Jorhat Engineering College, Assam, India.
Published Online: May-August 2026
Pages: 721-730
Cite this article
No DOIReferences
1. Dr. Dhrubajyoti Baruah, Anindita Boruah, "Analysis of Assamese Backed English Generated Sentiment: AABEG", Indian Journal of Computer Science and Technology, Volume 04, Issue 03 (September-December 2025), PP: 203-211.
2. N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2005, pp. 886-893.
3. C. Tensmeyer and T. Martinez, "Historical Document Image Binarization Using Text Region Contrast," IEEE International Conference on Document Analysis and Recognition (ICDAR), 2017, pp. 115-120.
4. Ramesh, G., Shreyas, J., Balaji, J. M., Sharma, G. N., Gururaj, H. L., Srinidhi, N. N., Askar, S. S., & Abouhawwash, M. (2024). Hybrid manifold smoothing and label propagation technique for Kannada handwritten character recognition. Frontiers in Neuroscience, 18. https://doi.org/10.3389/fnins.2024.1362567
5. Keysers, D., Deselaers, T., Rowley, H. A., Wang, L. R., & Carbune, V. (2017). Multi-Language Online Handwriting Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(6), 1180-1194. https://doi.org/10.1109/tpami.2016.2572693
6. B. K. Tumut, "Documentation of Tai Ahom Manuscripts: Digital Archiving of Dead Language," DESIDOC Journal of Library & Information Technology, vol. 40, no. 5, pp. 286-291, 2020.
7. S. Chadha, "Ancient Text Character Recognition Using Deep Learning," International Journal of Engineering Research and Technology, vol. 13, no. 9, pp. 2177-2182, 2020.
8. A. H. Al-Ghraibah et al., "Ancient script recognition using machine learning with CNN algorithm in comparison with support vector machine (SVM)," AIP Conference Proceedings, vol. 3300, no. 1, Art. no. 020277, 2025.
9. H. Wang et al., "Ancient Chinese Character Recognition with Improved Swin-Transformer and Flexible Data Enhancement Strategies," Applied Sciences, vol. 14, no. 7, p. 2932, 2024.
10. M. F. Rice, "Manuscripts Character Recognition Using Machine Learning and Deep Learning," J. Imaging, vol. 9, no. 4, p. 78, 2023.
11. J. Edwards, "Linguistic Inclusivity in the Digital Age: Challenges for Low-Resource Computational Models," Journal of Digital Humanities, vol. 14, no. 2, pp. 102-115, 2022.
12. A. Khan et al., "A Survey on Deep Learning in Image Processing: Architectural Frameworks and Feature Extraction Capabilities," Computing Surveys, vol. 54, no. 4, pp. 1-33, 2021.
13. S. Naseer et al., "Vision Transformers for Pattern Recognition: A Review of Advancements in Paleography and Script Digitization," IEEE Access, vol. 11, pp. 43211-43228, 2023.
2. N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), 2005, pp. 886-893.
3. C. Tensmeyer and T. Martinez, "Historical Document Image Binarization Using Text Region Contrast," IEEE International Conference on Document Analysis and Recognition (ICDAR), 2017, pp. 115-120.
4. Ramesh, G., Shreyas, J., Balaji, J. M., Sharma, G. N., Gururaj, H. L., Srinidhi, N. N., Askar, S. S., & Abouhawwash, M. (2024). Hybrid manifold smoothing and label propagation technique for Kannada handwritten character recognition. Frontiers in Neuroscience, 18. https://doi.org/10.3389/fnins.2024.1362567
5. Keysers, D., Deselaers, T., Rowley, H. A., Wang, L. R., & Carbune, V. (2017). Multi-Language Online Handwriting Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(6), 1180-1194. https://doi.org/10.1109/tpami.2016.2572693
6. B. K. Tumut, "Documentation of Tai Ahom Manuscripts: Digital Archiving of Dead Language," DESIDOC Journal of Library & Information Technology, vol. 40, no. 5, pp. 286-291, 2020.
7. S. Chadha, "Ancient Text Character Recognition Using Deep Learning," International Journal of Engineering Research and Technology, vol. 13, no. 9, pp. 2177-2182, 2020.
8. A. H. Al-Ghraibah et al., "Ancient script recognition using machine learning with CNN algorithm in comparison with support vector machine (SVM)," AIP Conference Proceedings, vol. 3300, no. 1, Art. no. 020277, 2025.
9. H. Wang et al., "Ancient Chinese Character Recognition with Improved Swin-Transformer and Flexible Data Enhancement Strategies," Applied Sciences, vol. 14, no. 7, p. 2932, 2024.
10. M. F. Rice, "Manuscripts Character Recognition Using Machine Learning and Deep Learning," J. Imaging, vol. 9, no. 4, p. 78, 2023.
11. J. Edwards, "Linguistic Inclusivity in the Digital Age: Challenges for Low-Resource Computational Models," Journal of Digital Humanities, vol. 14, no. 2, pp. 102-115, 2022.
12. A. Khan et al., "A Survey on Deep Learning in Image Processing: Architectural Frameworks and Feature Extraction Capabilities," Computing Surveys, vol. 54, no. 4, pp. 1-33, 2021.
13. S. Naseer et al., "Vision Transformers for Pattern Recognition: A Review of Advancements in Paleography and Script Digitization," IEEE Access, vol. 11, pp. 43211-43228, 2023.
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