Inspiration
To solve the ongoing widespread problem of ineligible handwriting among doctors
What it does
It reads human handwriting
How we built it
Using swift
Challenges we ran into
The initial idea. There were sometimes when we had to do extra research to learn how to do and use calls since we were not too experienced.
Accomplishments that we're proud of
That we made something that actually has a purpose and uses in society.
What we learned
The most valuable thing we learned from today was teamwork, how if we work together and meet our goals then our team can do wonders. We learned how team management skills and also extended our knowledge of computer science.
What's next for Extractor
We will add a user feedback option if our program is unsuccessful at detecting the word(s). This would allow the computer to store what kind of mistakes it makes and make itself better over time.
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