Author:
Bayoudh S.,Mouchère H.,Miclet L.,Anquetil E.
Publisher
Springer Berlin Heidelberg
Reference16 articles.
1. Wolf, L., Martin, I.: Robust boosting for learning from few examples. In: IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), IEEE Computer Society Press, Los Alamitos (2005)
2. Bishop, C.: Training with noise is equivalent to Tikhonov regularization. Neural Computation 7(1), 108–116 (1995)
3. Cano, J., Pérez-Cortes, J.C., Arlandis, J., Llobet, R.: Training set expansion in handwritten character recognition. In: Proc. of the 9th Int. Workshop on Structural and Syntactic Pattern Recognition, pp. 548–556 (2002)
4. Simard, P., Steinkraus, D., Platt, J.C.: Best practice for convolutional neural network applied to visual analysis. In: Proc. of the 7th Int. Conf. on Document Analysis and Recognition (2003)
5. Varga, T., Bunke, H.: Generation of synthetic data for an HMM-based handwriting recognition system. In: Proc. of 7th Int. Conf. on Document Analysis and Recognition, pp. 618–622 (2003)
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A Survey on Arabic Handwritten Character Recognition;SN Computer Science;2020-05
2. Case-Based Reasoning, Analogy, and Interpolation;A Guided Tour of Artificial Intelligence Research;2020
3. An Analogical Interpolation Method for Enlarging a Training Dataset;Lecture Notes in Computer Science;2019
4. Experiments in Learning to Solve Formal Analogical Equations;Case-Based Reasoning Research and Development;2018
5. Generating synthetic handwriting using n-gram letter glyphs;Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing - ICVGIP '16;2016