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Enhancing handwritten text recognition accuracy with gated mechanisms.

Ravikumar Chinthaginjala1, C Dhanamjayulu2, Tai-Hoon Kim3

  • 1School of Electronics Engineering, Vellore Institute of Technology, Vellore, India. cvrkvit@gmail.com.

Scientific Reports
|July 22, 2024
PubMed
Summary
This summary is machine-generated.

Gated mechanisms like Long Short-Term Memory networks significantly improve Handwritten Text Recognition (HTR). This advancement enhances accuracy and robustness for digitizing historical documents and more.

Keywords:
Convolutional recurrent neural networksDeep learningGated convolutional neural networksHandwritten transcript recognitionNatural language processing

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Machine Learning

Background:

  • Handwritten Text Recognition (HTR) is complex due to inherent variations.
  • Traditional HTR methods face challenges in accuracy and robustness.

Purpose of the Study:

  • To provide an overview of Handwritten Text Recognition (HTR) using gated mechanisms.
  • To highlight the novelty and advantages of gated mechanisms in HTR systems.

Main Methods:

  • Utilizing gated mechanisms, specifically Long Short-Term Memory (LSTM) networks, for sequence modeling.
  • Implementing a pipeline involving image preprocessing, feature extraction, gated mechanism modeling, and decoding.
  • Training with annotated datasets and optimization techniques to minimize errors.

Main Results:

  • Gated mechanisms enable capturing long-term dependencies and handling variable-length sequences.
  • Improved accuracy and robustness in HTR compared to traditional approaches.
  • Demonstrated superior performance against the latest HTR iteration on five diverse datasets.

Conclusions:

  • Gated mechanisms offer significant advancements for effective Handwritten Text Recognition.
  • This technology has broad applications, including digitizing historical documents and real-time transcription.
  • Enables low-cost computing devices like smartphones and robots to benefit from advanced HTR.