If the input to the autoencoder is normalized, do we need to use sigmoid on the last layer?
According to: https://stackoverflow.com/questions/65307833/why-is-the-decoder-in-an-autoencoder-uses-a-sigmoid-on-the-last-layer
- The last layer activation function contains sigmoid in order to the output to be in range [0, 1].
- If the input to the autoencoder is normalized (each pixel between [0..1]), Can we change the activation function of the last layer from sigmoid to be something else ?
- Can we use no activation function at all ?
Topic sigmoid activation-function autoencoder deep-learning machine-learning
Category Data Science