A comprehensive study of auto-encoders for anomaly detection ...
Sep 1, 2024 · Deep learning architectures, particularly Variational Auto-encoders (VAEs) and Generative Adversarial Networks (GANs), have emerged as powerful tools for producing …
SA2E-AD: A Stacked Attention Autoencoder for Anomaly Detection …
To address this problem, we propose a stacked attention autoencoder for anomaly detection in multivariate time series (SA2E-AD); it focuses on fully utilizing the metrical and temporal …
An attention graph stacked autoencoder for anomaly detection …
Sep 1, 2024 · The proposed attention graph stacked autoencoder based on reconstruction loss for anomaly detection task is a combination of attention graph convolution and stacked …
An Anomaly Detection Method for UAV Based on Wavelet
May 14, 2024 · Firstly, we use wavelet decomposition to denoise the original data; then, we used the stacked denoising autoencoder to achieve feature extraction. Finally, the softmax classifier …
Anomaly Detection for Semiconductor Tools Using Stacked Autoencoder ...
This paper proposes a Stacked Autoencoder Learning for Anomaly Detection (SALAD) framework that enables anomaly detection in realtime by using a multidimensional time-frequency …
Hyperspectral anomaly detection based on stacked denoising …
Sep 5, 2017 · To overcome this problem, a method of hyperspectral AD based on stacked denoising autoencoders (AE) (HADSDA) is proposed. Simultaneously, two different feature …
Advancing Autoencoder Architectures for Enhanced Anomaly Detection …
In this paper, we propose a hybrid autoencoder model, called ConvBiLSTM-AE, which combines convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM) to …
Stacked-Autoencoder Based Anomaly Detection with Industrial Control ...
Feb 3, 2021 · In this paper, we proposed a stacked-autoencoder (SAE), deep Support Vector Data Description (SVDD)-based data anomaly detection technique using an ICS dataset …
Augmenting cybersecurity through attention based stacked autoencoder ...
Dec 28, 2024 · For the detection and mitigation of attack, the presented CASAE-POADMA approach employs the attention-based stacked autoencoder (ASAE) method. Eventually, the …
A Stacked Autoencoder Neural Network based Automated Feature Extraction ...
In this work, we have developed an automated feature extraction method for on-line condition monitoring based on the stack of the traditional autoencoder and an on-line sequential …
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