This is my attempt at classifying images in the cifar10 dataset. It’s based around 3inception modules.
Accuracy
Architecture |
Accuracy on test set |
---|---|
c2, c2, mp, c2,c2,mp,f,d,d |
xx |
c2, ap, c2, ap, c2, ap, f, d, d, do |
64.28 %, 60.22 % |
data-normalized, c2, ap, c2, ap, c2, ap, f, d, d, do |
65.83 % |
data-normalized-gray, c2, ap, c2, ap, c2, ap, f, d, d, do |
62.91 % |
inception-module |
62.82 % (stopped becuase of overfitting) |
inception dense drop |
62.89 % |
inception inception drop |
74.18 % |
inceptionx3 dense drop |
77.61 % |
nceptionx3 dense drop dense drop dense |
77.25 % |
Git
https://github.com/Tzeny/udemy-zero-to-deep-learning/blob/master/course/Cifar10.ipynb