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Related Concept Videos

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Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
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Pashtu Language Digits Dataset.

Rehan Ullah Khan1, Khalil Khan2,3

  • 1Department of Information Technology, College of Computer, Qassim University, Buraydah, Saudi Arabia.

Data in Brief
|November 25, 2022
PubMed
Summary
This summary is machine-generated.

Researchers developed a new dataset of 50,000 Pashtu handwritten digits to advance Optical Character Recognition (OCR) technology for this under-resourced language.

Keywords:
Machine Learning, MLMachine learningNatural Language Processing, NLPNatural language processingOptical character recognitionPashtu Language Digits Dataset, PLDDText recognition

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Natural Language Processing

Background:

  • Pashtu is spoken by 50 million people globally, serving as the national language of Afghanistan and spoken in Pakistan.
  • Existing Optical Character Recognition (OCR) research is limited for Pashtu, necessitating development of specialized systems.
  • The complex calligraphy of Pashtu presents unique challenges for automated character recognition.

Purpose of the Study:

  • To introduce and publicly release a comprehensive dataset of handwritten Pashtu digits.
  • To facilitate the development of a mature Optical Character Recognition (OCR) system for the Pashtu language.
  • To support research in low-resource language OCR and machine learning.

Main Methods:

  • Collected and scanned 50,000 handwritten Pashtu digits from 1250 diverse participants (male and female).
  • Ensured data diversity by including faculty, staff, and students from an academic institution.
  • Made the dataset publicly available for research and development purposes.

Main Results:

  • A novel, large-scale dataset of 50,000 Pashtu handwritten digits is now available.
  • The dataset comprises images collected from a wide demographic range, ensuring representativeness.
  • This resource is poised to accelerate progress in Pashtu OCR development.

Conclusions:

  • The availability of this dataset is a significant step towards creating robust Pashtu OCR systems.
  • It addresses a critical gap in resources for low-resource language technology.
  • The dataset will empower researchers to build and improve machine recognition of Pashtu script.