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Related Experiment Video

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Convolutional neural network-based ensemble methods to recognize Bangla handwritten character.

Mir Moynuddin Ahmed Shibly1, Tahmina Akter Tisha1, Tanzina Akter Tani1

  • 1Department of Computer Science and Engineering, East West University, Dhaka, Bangladesh.

Peerj. Computer Science
|July 26, 2021
PubMed
Summary
This summary is machine-generated.

This study developed an efficient Bangla handwritten character classifier using deep learning. The stacked generalization ensemble method achieved high accuracy, paving the way for automated handwriting recognition systems.

Keywords:
Bangla handwritten character recognitionBootstrap aggregatingConvolutional neural networkDeep learningEnsemble learningFeature extractionImage classificationStacked generalization

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Machine Learning

Background:

  • Advancements in deep learning enable autonomous systems for text recognition.
  • Bangla handwritten text extraction has diverse applications, including post-office automation and signboard recognition.
  • An efficient isolated Bangla handwritten character classifier is crucial for developing such systems.

Purpose of the Study:

  • To classify handwritten Bangla characters using deep learning and ensemble methods.
  • To identify the best performing convolutional neural network (CNN) architecture for feature extraction.
  • To enhance classification performance through ensemble techniques.

Main Methods:

  • Development of seven CNN-based architectures for initial classification.
  • Utilizing the best CNN model as a feature extractor for shallow machine learning algorithms.
  • Application of five ensemble methods, including stacked generalization, to improve classification accuracy.

Main Results:

  • The stacked generalization ensemble method achieved superior performance.
  • Achieved accuracy, precision, and recall of 98.68%, 98.69%, and 98.68% respectively on the Ekush dataset.
  • Consistent results were obtained on the BanglaLekha-Isolated dataset, validating the approach.

Conclusions:

  • Deep learning, particularly CNNs and ensemble methods, is effective for large-scale Bangla handwritten character recognition.
  • The proposed system significantly advances the field of handwritten text automation.
  • This research provides a robust foundation for future developments in Bangla character recognition.