Employs neural networks to classify images into four categories: ship, automobile, dog or frog

Overview

Neural Net Image Classifier

Employs neural networks to classify images into four categories: ship, automobile, dog or frog

Viterbi_1.py uses a classic shallow classic network with an accuracy of ~62%.

Viterbi_2.py uses a modern network with L2 Regulation and Convolutional Neural Networks with an accuracy of ~ 83%.

Viterbi_3.py is adapted to the testing data set using a specific combination of convolutional neural networks and activation functions with an accuracy of ~87%. (This could be improved upon with further testing).

Owner
Riley Baker
Computer Engineering, James Scholar Honors Student, Specializing in A.I and ML
Riley Baker
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