Binarizing Documents by Leveraging both Space and Frequency
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-70543-4_1
Reference80 articles.
1. Akbari, Y., Al-Maadeed, S., Adam, K.: Binarization of degraded document images using convolutional neural networks and wavelet-based multichannel images. IEEE Access 8, 153517–153534 (2020)
2. Akbari, Y., Britto, A.S., Al-Maadeed, S., Oliveira, L.S.: Binarization of degraded document images using convolutional neural networks based on predicted two-channel images. In: ICDAR (2019)
3. Ayatollahi, S.M., Nafchi, H.Z.: Persian heritage image binarization competition (PHIBC 2012). In: PRIA (2013)
4. Barron, J.T.: A general and adaptive robust loss function. In: CVPR (2019)
5. Lecture Notes in Computer Science;JT Barron,2020
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