Exploiting the latent space of deep AutoEncoders for the identification of signal pulses in noisy time-series

Gioacchino Alex Anastasi, Sebastiano Francesco Albergo, Marzio De Napoli +3

We propose a data-driven procedure, based on convolutional variational autoencoders, to identify the presence of signal pulses in long time-series. The dataset consists of syntheti…