Models for Quasi-Objective Rating of Digital Samples

How can we build machine learning models that can tell good handwriting from bad handwriting?

A project for researching and developing quasi-objective models to perform a human-like rating of digital samples, more specifically, handwriting samples. The project covers data collection via observational studies, theory-building of machine learning models, system development of prototypes, and finally, a real-world application experiment. The project is currently in an initial phase of data collection.

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