The dataset used consists of about 12600 images. Contrast Limited Adaptive Histogram Equalization is applied to all images before feeding them as input to the trained transforming auto-encoder.

Autoencoders enable us to distil information by utilising a neural network architecture composed of an encoder and decoder. There are multiple types of autoencoders that vary based on their structure ...

Model compression aims to deploy deep neural networks (DNN) on mobile devices with limited computing and storage resources. However, most of the existing model compression methods rely on manually ...

Python 3.7.9 PyTorch 1.6.0 (cuda 10.2) torchvision 0.7.0 torch-geometric 1.6.1 To evaluate the AGMC on the ILSVRC-2012 dataset, you need to first download the dataset from ImageNet and export the data ...

Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are unable to ...