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Image-to-Image
TF-Keras
pixelwise-segmentation
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@@ -7,14 +7,14 @@ license: apache-2.0
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  This is a CNN model for document image binarization. It can be
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  used to convert all pixels in a color or grayscale document image
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- to only black or white pixels. The main purpose is to improve the
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  contrast between foreground (text) and background (paper) for
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  purposes of OCR. The model is based on a `ResNet50-Unet` model.
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  # Results
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  In the *DocEng’2021 Time-Quality Binarization Competition*
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  ([paper](https://dib.cin.ufpe.br/docs/DocEng21_bin_competition_report.pdf)),
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- the model ranked 12 times under the top 8 of 63 methods in the, winning 2 tasks.
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  In the *ICDAR 2021 Competition on Time-Quality Document Image
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  Binarization* ([paper](https://dib.cin.ufpe.br/docs/papers/ICDAR2021-TQDIB_final_published.pdf)),
 
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  This is a CNN model for document image binarization. It can be
9
  used to convert all pixels in a color or grayscale document image
10
+ to only black or white pixels. The main aim is to improve the
11
  contrast between foreground (text) and background (paper) for
12
  purposes of OCR. The model is based on a `ResNet50-Unet` model.
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  # Results
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  In the *DocEng’2021 Time-Quality Binarization Competition*
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  ([paper](https://dib.cin.ufpe.br/docs/DocEng21_bin_competition_report.pdf)),
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+ the model ranked 12 times under the top 8 of 63 methods, winning 2 tasks.
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  In the *ICDAR 2021 Competition on Time-Quality Document Image
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  Binarization* ([paper](https://dib.cin.ufpe.br/docs/papers/ICDAR2021-TQDIB_final_published.pdf)),