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A high-performance neural engine for cross-cultural numerical recognition. By fusing the standard MNIST framework with a 23,000-image dataset of European handwritten notation, Ghost-Digit eliminates stylistic bias. Built on a tiered 872K-parameter CNN with multi-stage dropout, it is optimized for high-accuracy inference on real-world inputs.

  • Updated May 10, 2026
  • Python

The objective of this project is to develop multiple variations of AI algorithms that outperform random guessing and analyze their relative performance against each other. (This is a collaborative, final project for the “Intro to Artificial Intelligence” class at the University of South Florida).

  • Updated Jan 26, 2026
  • Python

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