Inspiration
Working alongside my groupmates inspired me to work even harder on the project. Talking about past project experiences helped us realise that there is a need for this product, which can help reduce manual labour and time.
What it does
Outsourcing data collection to the public. Our model will then identify if the data collected are appropriate to be used for future model training.
How we built it
We planned out and used what most of us are proficient in, which is Python language.
Challenges we ran into
Figuring out which software is feasible for our final hack. We planned to use the haar-based classifier initially for its speed and feature extraction, however, it lacked the prediction probability that we needed.
Accomplishments that we're proud of
Coming along as a team despite our diverse backgrounds and occasionally clashing ideas.
What we learned
Python, Machine Learning, Flutter, Prototyping in Figma
What's next for El-BaT
Creating an actual app for the software and getting more data to increase model accuracy.
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