The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Improving Offline Handwritten Text Recognition with Hybrid HMM/ANN Models
Abstract
This paper proposes the use of hybrid Hidden Markov Model (HMM)/Artificial Neural Network (ANN) models for recognizing unconstrained offline handwritten texts. The structural part of the optical models has been modeled with Markov chains, and a Multilayer Perceptron is used to estimate the emission probabilities. This paper also presents new techniques to remove slope and slant from handwritten text and to normalize the size of text images with supervised learning methods. Slope correction and size normalization are achieved by classifying local extrema of text contours with Multilayer Perceptrons. Slant is also removed in a nonuniform way by using Artificial Neural Networks. Experiments have been conducted on offline handwritten text lines from the IAM database, and the recognition rates achieved, in comparison to the ones reported in the literature, are among the best for the same task.
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Cites
Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
Greedy layer-wise training of deep networks
Bengio, Y., Lamblin, P., Popovici, D., & Larochelle, H. (2007) · Advances in Neural Information Processing Systems 19 · doi:10.7551/mitpress/7503.003.0024 · Cited by 4,841
Shortest path segmentation: A method for training a neural network to recognize character strings
Burges, C. J. C., Matan, O., Le Cun, Y., Denker, J. S., Jackel, L. D., Stenard, C. E., Nohl, C. R., & Ben, J. I. (2003) · [Proceedings 1992] IJCNN International Joint Conference on Neural Networks · doi:10.1109/ijcnn.1992.227175 · Cited by 37
Cited by
Word Spotting and Recognition with Embedded Attributes
Almazan, J., Gordo, A., Fornes, A., & Valveny, E. (2014) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2339814 · Cited by 517
Decoupled Attention Network for Text Recognition
Wang, T., Zhu, Y., Jin, L., Luo, C., Chen, X., Wu, Y., Wang, Q., & Cai, M. (2020) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v34i07.6903 · Cited by 294
Ordóñez, F. J., De Toledo, P., & Sanchis, A. (2013) · Sensors · doi:10.3390/s130505460 · Cited by 277
Metadata
- Authors
- España-Boquera, S., Castro-Bleda, M. J., Gorbe-Moya, J., & Zamora-Martinez, F.
- Venue
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Published
- 2011-04
- Volume
- 33
- Issue
- 4
- Pages
- 767-779
- ISSN
- 0162-8828 (ISSN-L)
- OpenAlex
- W2147393756
- Cited by
- 310
- References
- 3
- FWCI
- 19.16
- Type
- journal article
- Language
- en
- Open access
- closed
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- España-Boquera, S., Castro-Bleda, M. J., Gorbe-Moya, J., & Zamora-Martinez, F. (2011). Improving Offline Handwritten Text Recognition with Hybrid HMM/ANN Models. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2010.141
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