Apple's Face ID !!!

What it does

It takes a data set filled with animals, cars, planes, things, etc, and runs training data through layers of our Convolution Neural Network and outputs its training accuracy.

How I built it

In a team 4 during a Summer College Course, we took our mathmetical artificial intelligence knowledge and transfered in into a real neural network!

Challenges I ran into

Horrendous optimization and network adaptation. Incorrect structuring of CNN layers

Accomplishments that I'm proud of

Implementing a grayscale conversion solution. This was the solution that made this AI work

What I learned

Neural Networks literally work for no reason.

What's next for Image-Recognition-CIFAR-10

Identify harder images! Identify people! Face recognition!

Built With

Share this project: