Barnamala: Parameter-Efficient Handwritten Devanagari Recognition at Benchmark Saturation

arXiv cs.AI · 18 hours ago

Researchers built a compact 1.11 million parameter convolutional network that achieved 99.73% accuracy on Devanagari handwritten character recognition, matching the performance ceiling that larger models also reach. The model reaches an intrinsic error floor of 11 errors that no configuration can statistically improve upon, despite being 15.6 times smaller than previous state-of-the-art approaches. The work demonstrates that benchmark saturation has been reached for this dataset, with additional model scaling providing no meaningful performance gains.