Ensemble of Convolutional Neural Networks Trained with Different Activation Functions

Understand

Activation functions play a vital role in the training of Convolutional Neural Networks.

• For this reason, to develop efficient and performing functions is a crucial problem in the deep learning community.
• Key to these approaches is to permit a reliable parameter learning, avoiding vanishing gradient problems.
• The goal of this work is to propose an ensemble of Convolutional Neural Networks trained using several different activation functions.