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Comparing CNN and SVM for recognizing handwritten Devanāgarī script, using a dataset of 92,000 images. CNN achieved 98.66% accuracy, excelling in feature extraction, while SVM was faster but less precise (95.24%).

This project bridges linguistic gaps on Limbu languages through innovative NLP techniques, offering round-trip fidelity and collision handling.