Training a simple denoising autoencoder with 1d CNNs. The training data consisted of sine, square, sawtooth and sinc functions with additive white gaussian noise. The network, consisting of a few ...

We proposed a convolutional autoencoder with sequential and channel attention (CAE-SCA) to address this issue. Sequential attention (SA) is based on long short-term memory (LSTM), which captures ...

Image clustering is one of the challenging tasks in machine learning, and has been extensively used in various applications. Recently, various deep clustering methods has been proposed. These methods ...