Results 21 to 30 of about 113,519 (298)
Missing-Insensitive Short-Term Load Forecasting Leveraging Autoencoder and LSTM
IEEE Access, 2020 In most deep learning-based load forecasting, an intact dataset is required. Since many real-world datasets contain missing values for various reasons, missing imputation using deep learning is actively studied.
Kyungnam Park +3 more
doaj +1 more source
Autoencoding Variational Autoencoder
, 2020 Neurips ...
Cemgil, A. Taylan +4 more
openaire +2 more sources
BAE: Anomaly Detection Algorithm Based on Clustering and Autoencoder
Mathematics, 2023 In this paper, we propose an outlier-detection algorithm for detecting network traffic anomalies based on a clustering algorithm and an autoencoder model.
Dongqi Wang, Mingshuo Nie, Dongming Chen
doaj +1 more source
Autoencoder-PCA-based Online Supervised Feature Extraction-Selection Approach [PDF]
Journal of Artificial Intelligence and Data Mining, 2023 Due to the growing number of data-driven approaches, especially in artificial intelligence and machine learning, extracting appropriate information from the gathered data with the best performance is a remarkable challenge.
Amir Mehrabinezhad +2 more
doaj +1 more source
A novel GPU based intrusion detection system using deep autoencoder with Fruitfly optimization
SN Applied Sciences, 2021 Intrusion Detection Systems (IDSs) have received more attention to safeguarding the vital information in a network system of an organization. Generally, the hackers are easily entering into a secured network through loopholes and smart attacks.
R. Sekhar +3 more
doaj +1 more source
Background modeling by shifted tilings of stacked denoising autoencoders [PDF]
, 2019 The effective processing of visual data without interruption is currently of supreme importance. For that purpose, the analysis system must adapt to events that may affect the data quality and maintain its performance level over time.
A Elgammal +12 more
core +1 more source
Anomaly sign detection by monitoring thousands of process values using a two-stage autoencoder
Mechanical Engineering Journal, 2021 In a large-scale plant such as a nuclear power plant, thousands of process values are measured for the purpose of monitoring the plant performance and the health of various systems.
Susumu NAITO +7 more
doaj +1 more source
Feedback Recurrent Autoencoder [PDF]
ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 In this work, we propose a new recurrent autoencoder architecture, termed Feedback Recurrent AutoEncoder (FRAE), for online compression of sequential data with temporal dependency. The recurrent structure of FRAE is designed to efficiently extract the redundancy along the time dimension and allows a compact discrete representation of the data to be ...
Yang, Yang +3 more
openaire +2 more sources
Detection of Pitting in Gears Using a Deep Sparse Autoencoder
Applied Sciences, 2017 In this paper; a new method for gear pitting fault detection is presented. The presented method is developed based on a deep sparse autoencoder. The method integrates dictionary learning in sparse coding into a stacked autoencoder network.
Yongzhi Qu +3 more
doaj +1 more source
Physical Adversarial Attacks Against End-to-End Autoencoder Communication Systems
, 2019 We show that end-to-end learning of communication systems through deep neural network (DNN) autoencoders can be extremely vulnerable to physical adversarial attacks.
Larsson, Erik G., Sadeghi, Meysam
core +1 more source