DOI: 10.5281/zenodo.15130868
title: Persian Handwritten Digits Dataset

description: Description:

Discover the rich and intricate patterns of Persian Handwritten Digits Dataset with our extensive dataset, thoughtfully curated to provide an unparalleled resource for Al and machine learning applications. This comprehensive collection comprises 150,000 high-resolution images, each meticulously generated to represent the full spectrum of Persian digits from 0 to 9. Leveraging advanced Generative Adversarial Networks (GANs), these images capture the subtle nuances of Persian handwriting, offering both diversity and authenticity in each digit's representation.

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Dataset Highlights





Total Images: 150,000 high-quality images, offering a substantial dataset for robust model training and testing.




Class Distribution: 15,000 images per digit class (0-9), ensuring a balanced and representative dataset across all Persian numerals.




Image Resolution: Each image is rendered at a resolution of 28×28 pixels, ideal for a variety of machine learning tasks.




Authenticity: Images are created using state-of-the-art GANs, ensuring that each digit closely mimics real Persian handwriting with realistic variations.




Versatility: This dataset is perfectly suited for a wide range of applications, including but not limited to:




Digit recognition




Generative modeling




Handwriting analysis




OCR (Optical Character Recognition) systems development




Cultural studies in Persian script



Extended Features



Diverse Handwriting Styles: The dataset captures a variety of handwriting styles, from bold and precise to delicate and ornate, reflecting the cultural and individual diversity in Persian script.

Generative Learning Applications: The GAN-generated images serve as an excellent resource for those interested in exploring generative learning models, providing a rich dataset for experiments in generating or augmenting handwritten text.

Pre-Processed & Ready-to-Use: The dataset is pre-processed and ready for immediate use, eliminating the need for additional formatting or resizing, saving valuable time and effort in your Al projects.

Cultural and Linguistic Value: Beyond its technical applications, the dataset holds cultural significance, offering insights into Persian script, which can be valuable for linguists and cultural historians alike.


Applications

This dataset is an essential tool for:



Researchers: Dive into the complexities of Persian script and explore novel approaches in digit recognition or handwriting analysis.

Data Scientists: Enhance your machine learning models with a dataset that offers both quality and quantity, ensuring accurate and reliable outcomes.

Al Developers: Build and refine OCR systems tailored specifically for Persian script, or explore the potential of GANs in generating handwritten text.

Educators and Students: Utilize this dataset in academic settings to teach and learn about handwriting recognition, machine learning, and cultural studies.


Conclusion

Whether you're pioneering new frontiers in digit recognition, developing advanced OCR systems, or simply exploring the intersection of Al and cultural studies, the Persian Handwritten Digits dataset offers a wealth of possibilities. Its balanced, high-quality images and extensive class representation make it a valuable resource for anyone working with Persian script or interested in the broader field of handwritten digit recognition.

This dataset is sourced from Kaggle.