Open writer identification from handwritten text fragments using lite convolutional neural network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s10032-023-00458-3.pdf
Reference53 articles.
1. Rehman, A., Naz, S., Razzak, M.I.: Writer identification using machine learning approaches: a comprehensive review. Multimed. Tools Appl. 78(8), 10889–10931 (2019). https://doi.org/10.1007/s11042-018-6577-1
2. Gazzah, S., Essoukri Ben Amara, N.: Writer identification using modular MLP classifier and genetic algorithm for optimal features selection. In: International Symposium on Neural Networks, pp. 271–276 (2006). https://doi.org/10.1007/11760023 40. Springer
3. Djoudjai, M.A., Chibani, Y.: Open writer identification from offline handwritten signatures by jointing the one-class symbolic data analysis classifier and feature-dissimilarities. International Journal on Document Analysis and Recognition (IJDAR), 1–17 (2022). https://doi.org/10.1007/s10032-022-00403-w
4. Bensefia, A., Nosary, A., Paquet, T., Heutte, L.: Writer identification by writer’s invariants. In: Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition, pp. 274–279. IEEE (2002). https://doi.org/10.1109/IWFHR.2002.1030922
5. Huber, R.A., Headrick, A.M.: Handwriting Identification: Facts and Fundamentals. CRC Press, Cambridge (1999)
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