Abstract: This paper presents an approach for holistic handwritten Uyghur word recognition using convolutional neural networks (CNNs).
Convolutional neural networks let Simayi et al. (2017) have a very high word recognition accuracy, 99.31%, on 2344 words using holistic method. Li et al. (2016) ...
Holistic approach performs very well on a finite lexicon recognition task, while analytic approach has great potential to realize lexicon-free handwritten word ...
In this paper, an end-to-end holistic method based on deep convolutional neural network is proposed to recognize off-line Persian handwritten words.
Missing: Uyghur | Show results with:Uyghur
This paper proposed the deep learning based self-learned features to recognize 128 handwritten Uyghur characters forms. The first-hand online handwritten ...
Missing: Holistic | Show results with:Holistic
Mayire Ibrayim, Wujiahemaiti Simayi, Askar Hamdulla: Unconstrained online handwritten Uyghur word recognition based on recurrent neural networks and ...
Jun 30, 2015 · An approach to online handwriting word recognition using segmentation-based techniques is presented in this paper, referred to as ...
Handwritten trajectory is fed to the network without explicit or implicit character segmentation. The network is trained to transcribe the input word trajectory ...
Aug 23, 2023 · In this study, we propose a unified three-stage model for Uyghur language recognition. The model is developed using a self-constructed Uyghur text dataset.
H‐WordNet: a holistic convolutional neural network approach for handwritten word recognition · List of references · Publications that cite this publication.
Missing: Uyghur | Show results with:Uyghur