GitHub

NVIDIA-DIGITS /examples /autoencoder

An image autoencoder may be used to learn a compressed representation of an image. An autoencoder comprises two parts: an encoder, which learns a representation of the image, using fewer neurons than ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

The Data Science Lab Autoencoder Anomaly Detection Using PyTorch Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a ...
GitHub

GAN, AutoEncoder and PCA

Reduce dimensionality of MNIST dataset images and plot in 2D using PCA Reduce dimensionality of MNIST dataset images and plot in 2D using an AutoEncoder Generate fake hand-written digits using a GAN.
Frontiers

Generation and discrimination of autism MRI images based on autoencoder

This study aims to explore an autoencoder-based method for generating brain MRI images of patients with Autism Spectrum Disorder (ASD) and non-ASD individuals, and to discriminate ASD based on the ...
IEEE

DAAED: A Deep Autoencoder based Adversarial Example Detection Technique

Abstract: Deep Learning based intrusion detection systems are susceptible to adversarial examples which are maliciously perturbed data samples that can cause a trained intrusion detection system to ...
IEEE

Contrastive Semantic-Aware Masked Autoencoder for Point Cloud Self-Supervised Learning

Abstract: Masked Autoencoder (MAE) has shown remarkable potential in self-supervised representation learning for 3D point clouds. However, these methods primarily rely on point-level or low-level ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

Anomaly detection is the process of finding items in a dataset that are different in some way from the majority of the items. For example, you could examine a dataset of credit card transactions to ...