Why doesn't this CNN model need fetures for reducing overfitting?

I found this CNN model by Nvidia end-to-end-deeplearning and with training this model, I'm wondering why this model doesn't need to have dropout layers to reduce overfitting. Neither, this doesn't have activation function.

I know we can tune the number of epochs and it reduces overfitting. I'm curious why this model works better without those layers?

Topic nvidia cnn deep-learning

Category Data Science

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