A new study published on arXiv investigates the efficiency of annotation for handwritten Devanagari text recognition. Researchers measured how many transcriptions are needed to make a recognizer useful, comparing four pretraining regimes. Supervised synthetic pretraining achieved a 0.50 Character Error Rate with only 81 transcribed words, significantly outperforming random initialization which required 355 words. The study also found that while pretraining offers substantial savings, its advantage diminishes as target accuracy increases, and in some cases, masked image modeling showed negative transfer. AI
IMPACT This research provides insights into optimizing data annotation for specialized scripts, potentially reducing costs for AI model training.
RANK_REASON The cluster contains an academic paper detailing a study on machine learning methods. [lever_c_demoted from research: ic=1 ai=1.0]
- arXiv
- Character Error Rate
- Devanagari
- encoder
- Hugging Face
- masked image modelling
- random initialisation
- supervised synthetic pretraining
- zero-shot learning
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