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Topical issue (end)
Character skeleton as a pen trace model for recognition from reconstructed trace
S. P. Arseev, L. M. Mestetskiy Lomonosov Moscow State University, Moscow, 119991 Russia
Abstract:
The article studies the handwriting recognition problem and the reduction of the text recognition problem from a text image to the text recognition problem from the trace of a pen writing the text. We propose a method based on a medial representation and reconstructing the pen trace from the handwritten text image. The method is substantiated based on an experimental study of character recognition from character images and from the reconstructed and true pen traces.
Keywords:
deep learning, convolutional neural network, recurrent neural network, skeleton, character recognition, handwriting recognition.
Citation:
S. P. Arseev, L. M. Mestetskiy, “Character skeleton as a pen trace model for recognition from reconstructed trace”, Avtomat. i Telemekh., 2021, no. 11, 3–15; Autom. Remote Control, 82:11 (2021), 1835–1845
Linking options:
https://www.mathnet.ru/eng/at15825 https://www.mathnet.ru/eng/at/y2021/i11/p3
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Statistics & downloads: |
Abstract page: | 108 | Full-text PDF : | 1 | References: | 22 | First page: | 17 |
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