Analysis of Parameter Influence on CNN

I was curious about the real influence of parameter on CNN training result. And I want to see if the result aligns with the estimation. I used the MNIST dataset and tune the parameters based on an old network called LeNet-5. CNN Layer The CNN layout is mostly the same as LeNet-5, with small modifications, for example, adding Dropout to avoid overfitting. The reason that I used LeNet-5 is mostly that it’s small and can train at a super fast speed with little GPU requirement[…]

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Dog classification using CNN transfer learning

This is the project I did in ECE 539 class. The result is pretty good, and I wish to show the result I have achieved. Introduction The primary task of this project is to use Convolution Neural Network (CNN) to identify different types of dogs base on their images. The Dataset This project uses Stanford Dogs Dataset. 20,580 images from 120 species are used in the project. As the result of the size of the dataset, I used transfer-learning strategy rather than training from the sketch.[…]

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