A naukri.com initiative
Arxiv
2d
101
Image Credit: Arxiv
Devanagari Digit Recognition using Quantum Machine Learning
- Handwritten digit recognition in regional scripts, like Devanagari, is essential for various purposes.
- Conventional models face challenges due to the script's complexity and limited annotated datasets.
- This paper presents a hybrid quantum-classical architecture for Devanagari handwritten digit recognition.
- The architecture combines a 10-qubit variational quantum circuit (VQC) with a convolutional neural network (CNN) for spatial feature extraction.
- The model achieves a quantum test accuracy of 99.80% and a test loss of 0.2893 on the Devanagari Handwritten Character Dataset.
- The average per-class F1-score achieved by the model is 0.9980.
- Compared to classical CNNs, the proposed model demonstrates better accuracy with fewer parameters and improved robustness.
- By utilizing quantum principles like superposition and entanglement, this work sets a new standard for regional script recognition.
- The research highlights the potential of quantum machine learning (QML) in low-resource language settings.
- The model's performance showcases promising implications for multilingual document digitization, educational tools, and cultural heritage preservation.
Read Full Article
6 Likes
For uninterrupted reading, download the app