A human-guided image-generation tool with contrastive multi-modal projection and sample-level prompt feedback lifted classification accuracy from 48.45% to 81.80% in a 10-class pet case study.
Arias-Hernandez, L
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Human-Guided Image Generation for Expanding Small-Scale Training Image Datasets
A human-guided image-generation tool with contrastive multi-modal projection and sample-level prompt feedback lifted classification accuracy from 48.45% to 81.80% in a 10-class pet case study.