ORGANIZING AND REPRESENTING A COLLECTION OF FONTS ACCORDING TO VISUAL SIMILARITY UTILIZING MACHINE LEARNING
Abstract:
The present disclosure relates to systems, methods, and non-transitory computer readable media for utilizing a visual-feature-classification model to generate font maps that efficiently and accurately organize fonts based on visual similarities. For example, the disclosed systems can extract features from fonts of varying styles and utilize a self-organizing map (or other visual-feature-classification model) to map extracted font features to positions within font maps. Further, the disclosed systems can also magnify areas of font maps by mapping some fonts within a bounded area to positions within a higher-resolution font map. Additionally, the disclosed systems can navigate the font map to identify visually similar fonts (e.g., fonts within a threshold similarity).
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