ARCHIVES

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on Pattern Analysis and Machine Intelligence, 22(1), 63-84.
2. Trier, Ø. D., Jain, A. K., & Taxt, T. (1996). Feature extraction methods for character recognition—A survey. Pattern Recognition,
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3. Simard, P. Y., Steinkraus, D., & Platt, J. C. (2003). Best practices for convolutional neural networks applied to visual document
analysis. ICDAR.
4. Graves, A., & Schmidhuber, J. (2009). Offline handwriting recognition with multidimensional recurrent neural networks. NIPS.
5. Jindal, M., et al. (2015). Structural features for handwritten Devanagari character recognition. Journal of Intelligent Systems, 24(4),
457-471.
6. Balci B, Saadati D, Shiferaw D (2017) Handwritten text recognition using deep learning. In: CS231n: Convolutional Neural Networks
for Visual Recognition, Stanford University, Course Project Report, Spring, pp 752–759.
7. Krishnan P, Jawahar C (2016) Matching handwritten document images. In: Proceedings of 14th European conference computer
vision—ECCV Part I 2016, Amsterdam, The Netherlands, October 11–14.
8. Krishnan P, Jawahar C (2016) Matching handwritten document images. In: European conference on computer vision.
9. Jayaraman PK, Mei J, Cai J, Zheng J (2018) Quadtree convolutional neural networks. In: Proceedings of the European conference
on computer vision (ECCV).
10. Li Y, Li Z, Qiu Q (2016) Assisting fuzzy offline handwriting recognition using recurrent belief propagation. In: 2016 IEEE symposium
series on computational intelligence (SSCI).
11. Maitra DS, Bhattacharya U, Parui SK (2015) A CNN-based common approach to handwritten character recognition of multiple
scripts. In: 2015 13th International conference on document analysis and recognition (ICDAR).
12. LeCun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998). Gradient-based learning applied to document recognition. Proceedings of
the IEEE.
13. Graves, A., & Schmidhuber, J. (2009). Offline handwriting recognition with multidimensional recurrent neural networks. NIPS.
14. Shi, B., Bai, X., & Yao, C. (2017). An end-to-end trainable neural network for image-based sequence recognition and its application
to scene text recognition. TPAMI.
15. Bhunia, A. K., et al. (2021). Handwriting recognition in low-resource scripts using adversarial learning. AAAI.
16. Sabour, S., Frosst, N., & Hinton, G. E. (2017). Dynamic routing between capsules. NIPS.
17. Jindal, M., & Gupta, V. (2019). Transfer learning-based approach for offline handwritten Gurmukhi character recognition. Procedia
Computer Science.
18. Freeman, H. (1961). On the encoding of arbitrary geometric configurations. IRE Transactions on Electronic Computers, EC-10(2),
260–268.
19. Jain, A. K., & Bhattacharjee, S. (1992). Text segmentation using Gabor filters for automatic document processing. Machine Vision
and Applications, 5(3), 169–184.
20. Dalal, N., & Triggs, B. (2005). Histograms of Oriented Gradients for Human Detection. CVPR, 886–893. (Used in OCR and character
recognition too.)
21. Sadjadi, F. A., & Hall, E. L. (1980). Three-dimensional moment invariants. IEEE Transactions on Pattern Analysis and Machine
Intelligence, (2), 127–136.
22. Kimura, F., Shridhar, M., & Takasawa, K. (1993). Segmentation-free handwritten numeral recognition with structural and statistical
features. Pattern Recognition, 27(6), 1049–1055.
23. Patil, V. H., & Nandgaonkar, A. P. (2014). Character recognition using vertical and horizontal projection feature with neural
network. IJERT, 3(2), 1816–1819.
24. Pradeep, J., Srinivasan, E., & Himavathi, S. (2011). Diagonal based feature extraction for handwritten character recognition system
using neural network. International Journal of Computer Applications, 8(9), 35–40.
25. Nagy, G. (1980). At the frontiers of OCR. Proceedings of the IEEE.
26. Liu, C.-L., Nakashima, K., Sako, H., & Fujisawa, H. (2004). Handwritten digit recognition: Benchmarking of state-of-the-art
techniques. Pattern Recognition.
27. Plamondon, R., & Srihari, S. N. (2000). Online and offline handwriting recognition: A comprehensive survey. IEEE T-PAMI.
28. Tappert, C. C., Suen, C. Y., & Wakahara, T. (1990). The state of the art in online handwriting recognition. IEEE T-PAMI.
29. Dutta, A., & Chaudhuri, B. B. (1993). A fuzzy approach to handwritten Devanagari character recognition. Proceedings of the 2nd
Int. Conf. on Document Analysis and Recognition (ICDAR).
30. Haupt, R. L., & Haupt, S. E. (2004). Practical Genetic Algorithms. Wiley.
31. Kim, G., & Kim, V. (2000). Hierarchical decision making for handwritten character recognition: Combination of global and local
decisions. Pattern Recognition Letters.
32. Srihari, S. N. (1993). Use of lexicons in recognizing handwritten words. Document Recognition II, SPIE