DropFilter: Dropout for Convolutions

Understand

Using a large number of parameters , deep neural networks have achieved remarkable performance on computer vison and natural language processing tasks.

• However the networks usually suffer from overfitting by using too much parameters.
• Dropout is a widely use method to deal with overfitting.
• Although dropout can significantly regularize densely connected layers in neural networks, it leads to suboptimal results when using for convolutional layers.