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SotA/Adversarial/Handwritten Text Recognition

Handwritten Text Recognition

20 benchmarks139 papers

Handwritten Text Recognition (HTR) is the task of automatically identifying and transcribing handwritten text from images or scanned documents into machine-readable text. The goal is to develop a system capable of accurately interpreting diverse handwriting styles, accounting for variations in alignment, stroke, spacing, and noise. This task involves detecting handwritten regions within an image, extracting the text content, and converting it into a structured digital format, enabling further search, indexing, or data analysis.

Benchmarks

Handwritten Text Recognition on IAM

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Handwritten Text Recognition on LAM(line-level)

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Handwritten Text Recognition on IAM(line-level)

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Handwritten Text Recognition on READ2016(line-level)

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Handwritten Text Recognition on Belfort

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Handwritten Text Recognition on READ 2016

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Handwritten Text Recognition on Bentham

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Handwritten Text Recognition on Digital Peter

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Handwritten Text Recognition on HKR

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Handwritten Text Recognition on IAM-B

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Handwritten Text Recognition on IAM-D

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Handwritten Text Recognition on SIMARA

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Handwritten Text Recognition on Saint Gall

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