Optimizing Performance of Feedforward and Convolutional Neural Networks through Dynamic Activation Functions. (arXiv:2308.05724v1 [cs.LG])

Deep learning training training algorithms are a huge success in recent years
in many fields including speech, text,image video etc. Deeper and deeper layers
are proposed with huge success with resnet structures having around 152 layers.
Shallow convolution neural networks(CNN's) are still an active research, where
some phenomena are still unexplained. Activation functions used in the network
are of utmost importance, as they provide non linearity to the networks. Relu's
are the most commonly used activation function.We show a complex …

algorithms arxiv cnn convolution convolutional neural networks deep learning deep learning training dynamic etc fields functions image networks neural networks performance research resnet speech success text through training video