Few Shots Are All You Need: A Progressive Few Shot Learning Approach for Low Resource Handwritten Text Recognition

M. S. T. Jaakkola, M. Szummer, Partially labeled classification with markov random walks, Advances in neural information processing systems (NIPS) 14 (2002) 945–952

2002

Earlier work this paper cites.

A. Graves, S. Fernández, F. Gomez, J. Schmidhuber, Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks, in: Proceedings of the 23rd international conference on Machine learning, 2006, pp. 369–376

2006

Earlier work this paper cites.

A. Graves, Offline arabic handwriting recognition with multidimensional recurrent neural networks, in: Guide to OCR for Arabic scripts, Springer, 2012, pp. 297–313

2012

Earlier work this paper cites.

J. Weston, F. Ratle, H. Mobahi, R. Collobert, Deep learning via semi-supervised embedding, in: Neural networks: Tricks of the trade, Springer, 2012, pp. 639–655

2012

Earlier work this paper cites.

V. Frinken, M. Baumgartner, A. Fischer, H. Bunke, Semi-supervised learning for cursive handwriting recognition using keyword spotting, in: 2012 International Conference on Frontiers in Handwriting Recognition, IEEE, 2012, pp. 49–54

2012

Earlier work this paper cites.

D.-H. Lee, et al., Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks, in: Workshop on challenges in representation learning, ICML, Vol. 3, 2013

2013

Earlier work this paper cites.

L. Rothacker, D. Fisseler, G. G. Müller, F. Weichert, G. A. Fink, Retrieving cuneiform structures in a segmentation-free word spotting framework, in: Proceedings of the 3rd International Workshop on Historical Document Imaging and Processing, 2015, pp. 129–136

2015

Earlier work this paper cites.

B. M. Lake, R. Salakhutdinov, J. B. Tenenbaum, Human-level concept learning through probabilistic program induction, Science 350 (6266) (2015) 1332–1338

2015

Cited alongside, same era.

B. Bogacz, N. Howe, H. Mara, Segmentation free spotting of cuneiform using part structured models, in: 2016 15th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, 2016, pp. 301–306

2016

Cited alongside, same era.

A. Fornés, B. Megyesi, J. Mas, Transcription of encoded manuscripts with image processing techniques, in: Digital Humanities Montreal, Canada, August 8-11, 2017., 2017

2017

Cited alongside, same era.

B. Megyesi, N. Blomqvist, E. Pettersson, The decode database: Collection of historical ciphers and keys, in: The 2nd International Conference on Historical Cryptology, HistoCrypt 2019, June 23-26 2019, Mons, Belgium, 2019, pp. 69–78

2019

Cited alongside, same era.

J. Choi, M. Jeong, T. Kim, C. Kim, Pseudo-labeling curriculum for unsupervised domain adaptation, in: British Machine Vision Conference (BMVC), Springer, 2019

2019

Later among the works it cites.

B. Megyesi, B. Esslinger, A. Fornés, N. Kopal, B. Láng, G. Lasry, K. d. Leeuw, E. Pettersson, A. Wacker, M. Waldispühl, Decryption of historical manuscripts: the decrypt project, Cryptologia 44 (6) (2020) 545–559

2020

Later among the works it cites.

Y. Wang, Q. Yao, J. T. Kwok, L. M. Ni, Generalizing from a few examples: A survey on few-shot learning, ACM Computing Surveys (CSUR) 53 (3) (2020) 1–34

2020

Later among the works it cites.

C. Zhang, A. Gupta, A. Zisserman, Adaptive text recognition through visual matching, in: ECCV, 2020, pp. 51–67

2020

Later among the works it cites.

G. Leifert, R. Labahn, J. A. Sánchez, Two semi-supervised training approaches for automated text recognition, in: 2020 17th International Conference on Frontiers in Handwriting Recognition (ICFHR), IEEE, 2020, pp. 145–150