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Convolutional Autoencoders are a type of neural network architecture that combines convolutional layers for feature extraction with transpose convolutional layers for upsampling, making them ...
Specifically, we'll design a neural network architecture ... our autoencoder ‘variational’. It comprises an encoder, decoder, with the latent representation reparameterized in between. Encoder — The ...
Abstract: In the remote sensing context spectral unmixing is a technique to decompose a mixed pixel into two fundamental representatives ... The proposed architecture consists of convolutional layers ...
Abstract: A convolutional spatiotemporal autoencoder is used for video anomaly detection. The proposed model architecture comprises ... implemented using three layers of deconvolutional layers. The ...
1 College of Information Engineering, Xinchuang Software Industry Base, Yancheng Teachers University, Yancheng, China. 2 Yancheng Agricultural College, Yancheng, China. Convolutional auto-encoders ...
There has been increasing interest in performing psychiatric brain imaging studies using deep learning. However, most studies in this field disregard three-dimensional (3D) spatial information and ...
La Trobe Institute for Molecular Sciences, La Trobe University, Bundoora, Victoria 3086, Australia Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia ...
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